Overview

Dataset statistics

Number of variables62
Number of observations93
Missing cells2298
Missing cells (%)39.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.2 KiB
Average record size in memory497.4 B

Variable types

Numeric12
Categorical41
Unsupported9

Alerts

airdate has constant value "2020-12-08" Constant
_embedded.show.externals.tvrage has constant value "19056.0" Constant
_embedded.show.dvdCountry.name has constant value "Japan" Constant
_embedded.show.dvdCountry.code has constant value "JP" Constant
_embedded.show.dvdCountry.timezone has constant value "Asia/Tokyo" Constant
url has a high cardinality: 93 distinct values High cardinality
name has a high cardinality: 85 distinct values High cardinality
_links.self.href has a high cardinality: 93 distinct values High cardinality
_embedded.show.url has a high cardinality: 66 distinct values High cardinality
_embedded.show.name has a high cardinality: 66 distinct values High cardinality
_embedded.show.premiered has a high cardinality: 53 distinct values High cardinality
_embedded.show.officialSite has a high cardinality: 58 distinct values High cardinality
_embedded.show.image.medium has a high cardinality: 62 distinct values High cardinality
_embedded.show.image.original has a high cardinality: 62 distinct values High cardinality
_embedded.show.summary has a high cardinality: 58 distinct values High cardinality
_embedded.show._links.self.href has a high cardinality: 66 distinct values High cardinality
_embedded.show._links.previousepisode.href has a high cardinality: 66 distinct values High cardinality
season is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with number and 4 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.network.id is highly correlated with seasonHigh correlation
season is highly correlated with rating.average and 1 other fieldsHigh correlation
number is highly correlated with _embedded.show.rating.averageHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with season and 6 other fieldsHigh correlation
_embedded.show.id is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 7 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with _embedded.show.externals.thetvdbHigh correlation
season is highly correlated with _embedded.show.externals.thetvdbHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 1 other fieldsHigh correlation
rating.average is highly correlated with number and 4 other fieldsHigh correlation
_embedded.show.id is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with number and 6 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.rating.averageHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 2 other fieldsHigh correlation
_embedded.show.updated is highly correlated with _embedded.show.rating.averageHigh correlation
id is highly correlated with url and 37 other fieldsHigh correlation
url is highly correlated with id and 46 other fieldsHigh correlation
name is highly correlated with id and 41 other fieldsHigh correlation
season is highly correlated with url and 20 other fieldsHigh correlation
number is highly correlated with url and 32 other fieldsHigh correlation
type is highly correlated with url and 18 other fieldsHigh correlation
airtime is highly correlated with id and 39 other fieldsHigh correlation
airstamp is highly correlated with id and 41 other fieldsHigh correlation
runtime is highly correlated with id and 41 other fieldsHigh correlation
summary is highly correlated with id and 44 other fieldsHigh correlation
rating.average is highly correlated with url and 27 other fieldsHigh correlation
_links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.type is highly correlated with id and 37 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 36 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with id and 39 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with url and 24 other fieldsHigh correlation
_embedded.show.weight is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 43 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 41 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with url and 33 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 32 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 46 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 46 other fieldsHigh correlation
image.medium is highly correlated with id and 44 other fieldsHigh correlation
image.original is highly correlated with id and 44 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 35 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 40 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 30 other fieldsHigh correlation
number has 14 (15.1%) missing values Missing
runtime has 4 (4.3%) missing values Missing
image has 93 (100.0%) missing values Missing
summary has 64 (68.8%) missing values Missing
rating.average has 86 (92.5%) missing values Missing
_embedded.show.language has 1 (1.1%) missing values Missing
_embedded.show.runtime has 19 (20.4%) missing values Missing
_embedded.show.averageRuntime has 2 (2.2%) missing values Missing
_embedded.show.ended has 56 (60.2%) missing values Missing
_embedded.show.officialSite has 9 (9.7%) missing values Missing
_embedded.show.rating.average has 86 (92.5%) missing values Missing
_embedded.show.network has 93 (100.0%) missing values Missing
_embedded.show.webChannel.id has 5 (5.4%) missing values Missing
_embedded.show.webChannel.name has 5 (5.4%) missing values Missing
_embedded.show.webChannel.country.name has 55 (59.1%) missing values Missing
_embedded.show.webChannel.country.code has 55 (59.1%) missing values Missing
_embedded.show.webChannel.country.timezone has 55 (59.1%) missing values Missing
_embedded.show.webChannel.officialSite has 28 (30.1%) missing values Missing
_embedded.show.dvdCountry has 93 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 92 (98.9%) missing values Missing
_embedded.show.externals.thetvdb has 42 (45.2%) missing values Missing
_embedded.show.externals.imdb has 53 (57.0%) missing values Missing
_embedded.show.image.medium has 4 (4.3%) missing values Missing
_embedded.show.image.original has 4 (4.3%) missing values Missing
_embedded.show.summary has 9 (9.7%) missing values Missing
_embedded.show.webChannel.country has 93 (100.0%) missing values Missing
image.medium has 63 (67.7%) missing values Missing
image.original has 63 (67.7%) missing values Missing
_embedded.show.network.id has 82 (88.2%) missing values Missing
_embedded.show.network.name has 82 (88.2%) missing values Missing
_embedded.show.network.country.name has 82 (88.2%) missing values Missing
_embedded.show.network.country.code has 82 (88.2%) missing values Missing
_embedded.show.network.country.timezone has 82 (88.2%) missing values Missing
_embedded.show.network.officialSite has 93 (100.0%) missing values Missing
_embedded.show._links.nextepisode.href has 87 (93.5%) missing values Missing
_embedded.show.image has 93 (100.0%) missing values Missing
_embedded.show.webChannel has 93 (100.0%) missing values Missing
_embedded.show.dvdCountry.name has 92 (98.9%) missing values Missing
_embedded.show.dvdCountry.code has 92 (98.9%) missing values Missing
_embedded.show.dvdCountry.timezone has 92 (98.9%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:39:18.504538
Analysis finished2022-09-06 02:39:37.719635
Duration19.22 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2032050.344
Minimum1960032
Maximum2380806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:37.794593image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1960032
5-th percentile1967819.4
Q11977637
median1983820
Q32008028
95-th percentile2298329.8
Maximum2380806
Range420774
Interquartile range (IQR)30391

Descriptive statistics

Standard deviation106080.2599
Coefficient of variation (CV)0.05220355894
Kurtosis3.009212077
Mean2032050.344
Median Absolute Deviation (MAD)6888
Skewness2.042625454
Sum188980682
Variance1.125302154 × 1010
MonotonicityNot monotonic
2022-09-05T21:39:37.917726image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19888571
 
1.1%
19776361
 
1.1%
19849461
 
1.1%
19849451
 
1.1%
19849441
 
1.1%
19849431
 
1.1%
19849421
 
1.1%
19849411
 
1.1%
19849401
 
1.1%
21751091
 
1.1%
Other values (83)83
89.2%
ValueCountFrequency (%)
19600321
1.1%
19604971
1.1%
19643321
1.1%
19645661
1.1%
19673491
1.1%
19681331
1.1%
19726041
1.1%
19735441
1.1%
19735451
1.1%
19760321
1.1%
ValueCountFrequency (%)
23808061
1.1%
23799271
1.1%
23369081
1.1%
23181001
1.1%
23110181
1.1%
22898711
1.1%
22877861
1.1%
22431831
1.1%
22396081
1.1%
21954111
1.1%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
https://www.tvmaze.com/episodes/1988857/sim-for-you-4x19-chanyeols-episode-19
 
1
https://www.tvmaze.com/episodes/1977636/to-love-1x25-episode-25
 
1
https://www.tvmaze.com/episodes/1984946/dream-detective-1x07-episode-7
 
1
https://www.tvmaze.com/episodes/1984945/dream-detective-1x06-episode-6
 
1
https://www.tvmaze.com/episodes/1984944/dream-detective-1x05-episode-5
 
1
Other values (88)
88 

Length

Max length152
Median length104
Mean length86.76344086
Min length58

Characters and Unicode

Total characters8069
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988857/sim-for-you-4x19-chanyeols-episode-19
2nd rowhttps://www.tvmaze.com/episodes/2007748/stand-up-autsajd-1x08-vana-ilin-malenkij-princ
3rd rowhttps://www.tvmaze.com/episodes/1986870/kotiki-1x07-seria-7
4th rowhttps://www.tvmaze.com/episodes/2008028/lab-s-antonom-belaevym-2x07-lev-lesenko
5th rowhttps://www.tvmaze.com/episodes/1964566/core-sense-1x10-episode-10

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988857/sim-for-you-4x19-chanyeols-episode-191
 
1.1%
https://www.tvmaze.com/episodes/1977636/to-love-1x25-episode-251
 
1.1%
https://www.tvmaze.com/episodes/1984946/dream-detective-1x07-episode-71
 
1.1%
https://www.tvmaze.com/episodes/1984945/dream-detective-1x06-episode-61
 
1.1%
https://www.tvmaze.com/episodes/1984944/dream-detective-1x05-episode-51
 
1.1%
https://www.tvmaze.com/episodes/1984943/dream-detective-1x04-episode-41
 
1.1%
https://www.tvmaze.com/episodes/1984942/dream-detective-1x03-episode-31
 
1.1%
https://www.tvmaze.com/episodes/1984941/dream-detective-1x02-episode-21
 
1.1%
https://www.tvmaze.com/episodes/1984940/dream-detective-1x01-episode-11
 
1.1%
https://www.tvmaze.com/episodes/2175109/wayward-guide-1x09-belly-of-the-beast1
 
1.1%
Other values (83)83
89.2%

Length

2022-09-05T21:39:38.039813image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988857/sim-for-you-4x19-chanyeols-episode-191
 
1.1%
https://www.tvmaze.com/episodes/1984030/world-war-two-week-by-week-s03-special-december-7-1941-pearl-harbor-minute-by-minute-in-real-time-part-9-1010am1
 
1.1%
https://www.tvmaze.com/episodes/1986870/kotiki-1x07-seria-71
 
1.1%
https://www.tvmaze.com/episodes/2008028/lab-s-antonom-belaevym-2x07-lev-lesenko1
 
1.1%
https://www.tvmaze.com/episodes/1964566/core-sense-1x10-episode-101
 
1.1%
https://www.tvmaze.com/episodes/2052507/wu-shen-zhu-zai-1x82-episode-821
 
1.1%
https://www.tvmaze.com/episodes/2096295/no-turning-back-romance-1x01-11
 
1.1%
https://www.tvmaze.com/episodes/1973544/please-wait-brother-1x23-episode-231
 
1.1%
https://www.tvmaze.com/episodes/1973545/please-wait-brother-1x24-episode-241
 
1.1%
https://www.tvmaze.com/episodes/2082173/ling-jian-zun-4x30-di130ji1
 
1.1%
Other values (83)83
89.2%

Most occurring characters

ValueCountFrequency (%)
e718
 
8.9%
-714
 
8.8%
t469
 
5.8%
/465
 
5.8%
s461
 
5.7%
o396
 
4.9%
w369
 
4.6%
a352
 
4.4%
i331
 
4.1%
m297
 
3.7%
Other values (30)3497
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5457
67.6%
Decimal Number1154
 
14.3%
Other Punctuation744
 
9.2%
Dash Punctuation714
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e718
13.2%
t469
 
8.6%
s461
 
8.4%
o396
 
7.3%
w369
 
6.8%
a352
 
6.5%
i331
 
6.1%
m297
 
5.4%
p283
 
5.2%
d230
 
4.2%
Other values (16)1551
28.4%
Decimal Number
ValueCountFrequency (%)
1229
19.8%
0171
14.8%
2163
14.1%
9123
10.7%
8106
9.2%
391
 
7.9%
483
 
7.2%
781
 
7.0%
662
 
5.4%
545
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/465
62.5%
.186
 
25.0%
:93
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-714
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5457
67.6%
Common2612
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e718
13.2%
t469
 
8.6%
s461
 
8.4%
o396
 
7.3%
w369
 
6.8%
a352
 
6.5%
i331
 
6.1%
m297
 
5.4%
p283
 
5.2%
d230
 
4.2%
Other values (16)1551
28.4%
Common
ValueCountFrequency (%)
-714
27.3%
/465
17.8%
1229
 
8.8%
.186
 
7.1%
0171
 
6.5%
2163
 
6.2%
9123
 
4.7%
8106
 
4.1%
:93
 
3.6%
391
 
3.5%
Other values (4)271
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII8069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e718
 
8.9%
-714
 
8.8%
t469
 
5.8%
/465
 
5.8%
s461
 
5.7%
o396
 
4.9%
w369
 
4.6%
a352
 
4.4%
i331
 
4.1%
m297
 
3.7%
Other values (30)3497
43.3%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM

Distinct85
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size872.0 B
Episode 8
 
2
Episode 23
 
2
Episode 2
 
2
Episode 5
 
2
Episode 26
 
2
Other values (80)
83 

Length

Max length79
Median length55
Mean length23.34408602
Min length1

Characters and Unicode

Total characters2171
Distinct characters127
Distinct categories9 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)82.8%

Sample

1st rowChanyeol's Episode 19
2nd rowВаня Ильин "Маленький принц"
3rd rowСерия 7
4th rowЛев Лещенко
5th rowEpisode 10

Common Values

ValueCountFrequency (%)
Episode 82
 
2.2%
Episode 232
 
2.2%
Episode 22
 
2.2%
Episode 52
 
2.2%
Episode 262
 
2.2%
Episode 252
 
2.2%
Episode 12
 
2.2%
Episode 72
 
2.2%
Episode 221
 
1.1%
Episode 211
 
1.1%
Other values (75)75
80.6%

Length

2022-09-05T21:39:38.160643image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode30
 
7.4%
minute20
 
4.9%
715
 
3.7%
14
 
3.4%
in12
 
2.9%
december12
 
2.9%
part10
 
2.5%
time10
 
2.5%
by10
 
2.5%
harbor10
 
2.5%
Other values (192)265
65.0%

Most occurring characters

ValueCountFrequency (%)
314
 
14.5%
e192
 
8.8%
i118
 
5.4%
a100
 
4.6%
o88
 
4.1%
r83
 
3.8%
n77
 
3.5%
t64
 
2.9%
s61
 
2.8%
l61
 
2.8%
Other values (117)1013
46.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1305
60.1%
Space Separator315
 
14.5%
Uppercase Letter279
 
12.9%
Decimal Number172
 
7.9%
Other Punctuation69
 
3.2%
Other Letter16
 
0.7%
Dash Punctuation13
 
0.6%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e192
14.7%
i118
 
9.0%
a100
 
7.7%
o88
 
6.7%
r83
 
6.4%
n77
 
5.9%
t64
 
4.9%
s61
 
4.7%
l61
 
4.7%
d50
 
3.8%
Other values (46)411
31.5%
Uppercase Letter
ValueCountFrequency (%)
E35
12.5%
M26
 
9.3%
T25
 
9.0%
P23
 
8.2%
H22
 
7.9%
D20
 
7.2%
R17
 
6.1%
A12
 
4.3%
S10
 
3.6%
I9
 
3.2%
Other values (25)80
28.7%
Other Letter
ValueCountFrequency (%)
و3
18.8%
ا2
12.5%
1
 
6.2%
د1
 
6.2%
1
 
6.2%
ب1
 
6.2%
م1
 
6.2%
ز1
 
6.2%
ی1
 
6.2%
ل1
 
6.2%
Other values (3)3
18.8%
Decimal Number
ValueCountFrequency (%)
143
25.0%
421
12.2%
021
12.2%
221
12.2%
717
 
9.9%
914
 
8.1%
89
 
5.2%
39
 
5.2%
69
 
5.2%
58
 
4.7%
Other Punctuation
ValueCountFrequency (%)
,26
37.7%
:21
30.4%
&5
 
7.2%
.5
 
7.2%
!4
 
5.8%
"4
 
5.8%
'3
 
4.3%
?1
 
1.4%
Space Separator
ValueCountFrequency (%)
314
99.7%
 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-13
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1441
66.4%
Common571
 
26.3%
Cyrillic143
 
6.6%
Arabic14
 
0.6%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e192
 
13.3%
i118
 
8.2%
a100
 
6.9%
o88
 
6.1%
r83
 
5.8%
n77
 
5.3%
t64
 
4.4%
s61
 
4.2%
l61
 
4.2%
d50
 
3.5%
Other values (45)547
38.0%
Cyrillic
ValueCountFrequency (%)
е15
 
10.5%
и12
 
8.4%
р11
 
7.7%
к10
 
7.0%
о10
 
7.0%
а9
 
6.3%
в7
 
4.9%
н6
 
4.2%
л6
 
4.2%
с5
 
3.5%
Other values (26)52
36.4%
Common
ValueCountFrequency (%)
314
55.0%
143
 
7.5%
,26
 
4.6%
:21
 
3.7%
421
 
3.7%
021
 
3.7%
221
 
3.7%
717
 
3.0%
914
 
2.5%
-13
 
2.3%
Other values (13)60
 
10.5%
Arabic
ValueCountFrequency (%)
و3
21.4%
ا2
14.3%
د1
 
7.1%
ب1
 
7.1%
م1
 
7.1%
ز1
 
7.1%
ی1
 
7.1%
ل1
 
7.1%
گ1
 
7.1%
ر1
 
7.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2002
92.2%
Cyrillic143
 
6.6%
Arabic14
 
0.6%
None10
 
0.5%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
314
 
15.7%
e192
 
9.6%
i118
 
5.9%
a100
 
5.0%
o88
 
4.4%
r83
 
4.1%
n77
 
3.8%
t64
 
3.2%
s61
 
3.0%
l61
 
3.0%
Other values (60)844
42.2%
Cyrillic
ValueCountFrequency (%)
е15
 
10.5%
и12
 
8.4%
р11
 
7.7%
к10
 
7.0%
о10
 
7.0%
а9
 
6.3%
в7
 
4.9%
н6
 
4.2%
л6
 
4.2%
с5
 
3.5%
Other values (26)52
36.4%
Arabic
ValueCountFrequency (%)
و3
21.4%
ا2
14.3%
د1
 
7.1%
ب1
 
7.1%
م1
 
7.1%
ز1
 
7.1%
ی1
 
7.1%
ل1
 
7.1%
گ1
 
7.1%
ر1
 
7.1%
None
ValueCountFrequency (%)
ö2
20.0%
ü2
20.0%
ô1
10.0%
à1
10.0%
 1
10.0%
À1
10.0%
å1
10.0%
ø1
10.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct13
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean241.4516129
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:38.251983image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)3

Descriptive statistics

Standard deviation654.9533756
Coefficient of variation (CV)2.712565751
Kurtosis3.856311171
Mean241.4516129
Median Absolute Deviation (MAD)1
Skewness2.402807182
Sum22455
Variance428963.9243
MonotonicityNot monotonic
2022-09-05T21:39:38.338440image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
143
46.2%
318
19.4%
202011
 
11.8%
27
 
7.5%
46
 
6.5%
101
 
1.1%
121
 
1.1%
181
 
1.1%
91
 
1.1%
81
 
1.1%
Other values (3)3
 
3.2%
ValueCountFrequency (%)
143
46.2%
27
 
7.5%
318
19.4%
46
 
6.5%
51
 
1.1%
71
 
1.1%
81
 
1.1%
91
 
1.1%
101
 
1.1%
121
 
1.1%
ValueCountFrequency (%)
202011
11.8%
311
 
1.1%
181
 
1.1%
121
 
1.1%
101
 
1.1%
91
 
1.1%
81
 
1.1%
71
 
1.1%
51
 
1.1%
46
6.5%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct39
Distinct (%)49.4%
Missing14
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean34.16455696
Minimum1
Maximum335
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:38.434893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median13
Q328
95-th percentile142.5
Maximum335
Range334
Interquartile range (IQR)23

Descriptive statistics

Standard deviation62.58848718
Coefficient of variation (CV)1.831971281
Kurtosis12.79290921
Mean34.16455696
Median Absolute Deviation (MAD)10
Skewness3.478102801
Sum2699
Variance3917.318728
MonotonicityNot monotonic
2022-09-05T21:39:38.541299image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
87
 
7.5%
75
 
5.4%
25
 
5.4%
15
 
5.4%
55
 
5.4%
34
 
4.3%
63
 
3.2%
143
 
3.2%
503
 
3.2%
233
 
3.2%
Other values (29)36
38.7%
(Missing)14
 
15.1%
ValueCountFrequency (%)
15
5.4%
25
5.4%
34
4.3%
42
 
2.2%
55
5.4%
63
3.2%
75
5.4%
87
7.5%
91
 
1.1%
102
 
2.2%
ValueCountFrequency (%)
3351
1.1%
2941
1.1%
2931
1.1%
1471
1.1%
1421
1.1%
1091
1.1%
981
1.1%
971
1.1%
821
1.1%
611
1.1%

type
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size872.0 B
regular
79 
significant_special
12 
insignificant_special
 
2

Length

Max length21
Median length7
Mean length8.849462366
Min length7

Characters and Unicode

Total characters823
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular79
84.9%
significant_special12
 
12.9%
insignificant_special2
 
2.2%

Length

2022-09-05T21:39:38.639583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:38.726134image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular79
84.9%
significant_special12
 
12.9%
insignificant_special2
 
2.2%

Most occurring characters

ValueCountFrequency (%)
r158
19.2%
a107
13.0%
e93
11.3%
g93
11.3%
l93
11.3%
u79
9.6%
i58
 
7.0%
n30
 
3.6%
s28
 
3.4%
c28
 
3.4%
Other values (4)56
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter809
98.3%
Connector Punctuation14
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r158
19.5%
a107
13.2%
e93
11.5%
g93
11.5%
l93
11.5%
u79
9.8%
i58
 
7.2%
n30
 
3.7%
s28
 
3.5%
c28
 
3.5%
Other values (3)42
 
5.2%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin809
98.3%
Common14
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
r158
19.5%
a107
13.2%
e93
11.5%
g93
11.5%
l93
11.5%
u79
9.8%
i58
 
7.2%
n30
 
3.7%
s28
 
3.5%
c28
 
3.5%
Other values (3)42
 
5.2%
Common
ValueCountFrequency (%)
_14
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII823
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r158
19.2%
a107
13.0%
e93
11.3%
g93
11.3%
l93
11.3%
u79
9.6%
i58
 
7.0%
n30
 
3.6%
s28
 
3.4%
c28
 
3.4%
Other values (4)56
 
6.8%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size872.0 B
2020-12-08
93 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters930
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-08
2nd row2020-12-08
3rd row2020-12-08
4th row2020-12-08
5th row2020-12-08

Common Values

ValueCountFrequency (%)
2020-12-0893
100.0%

Length

2022-09-05T21:39:38.798312image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:38.872714image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-0893
100.0%

Most occurring characters

ValueCountFrequency (%)
2279
30.0%
0279
30.0%
-186
20.0%
193
 
10.0%
893
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number744
80.0%
Dash Punctuation186
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2279
37.5%
0279
37.5%
193
 
12.5%
893
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2279
30.0%
0279
30.0%
-186
20.0%
193
 
10.0%
893
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2279
30.0%
0279
30.0%
-186
20.0%
193
 
10.0%
893
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
60 
20:00
17 
12:00
 
3
06:00
 
2
10:00
 
2
Other values (8)

Length

Max length5
Median length0
Mean length1.774193548
Min length0

Characters and Unicode

Total characters165
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)7.5%

Sample

1st row06:00
2nd row12:00
3rd row
4th row
5th row10:00

Common Values

ValueCountFrequency (%)
60
64.5%
20:0017
 
18.3%
12:003
 
3.2%
06:002
 
2.2%
10:002
 
2.2%
20:402
 
2.2%
08:001
 
1.1%
17:351
 
1.1%
07:001
 
1.1%
22:001
 
1.1%
Other values (3)3
 
3.2%

Length

2022-09-05T21:39:38.953708image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0017
51.5%
12:003
 
9.1%
06:002
 
6.1%
10:002
 
6.1%
20:402
 
6.1%
08:001
 
3.0%
17:351
 
3.0%
07:001
 
3.0%
22:001
 
3.0%
08:301
 
3.0%
Other values (2)2
 
6.1%

Most occurring characters

ValueCountFrequency (%)
087
52.7%
:33
 
20.0%
225
 
15.2%
17
 
4.2%
53
 
1.8%
62
 
1.2%
42
 
1.2%
82
 
1.2%
72
 
1.2%
32
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number132
80.0%
Other Punctuation33
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
087
65.9%
225
 
18.9%
17
 
5.3%
53
 
2.3%
62
 
1.5%
42
 
1.5%
82
 
1.5%
72
 
1.5%
32
 
1.5%
Other Punctuation
ValueCountFrequency (%)
:33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common165
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
087
52.7%
:33
 
20.0%
225
 
15.2%
17
 
4.2%
53
 
1.8%
62
 
1.2%
42
 
1.2%
82
 
1.2%
72
 
1.2%
32
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
087
52.7%
:33
 
20.0%
225
 
15.2%
17
 
4.2%
53
 
1.8%
62
 
1.2%
42
 
1.2%
82
 
1.2%
72
 
1.2%
32
 
1.2%

airstamp
Categorical

HIGH CORRELATION

Distinct19
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Memory size872.0 B
2020-12-08T12:00:00+00:00
63 
2020-12-08T17:00:00+00:00
 
5
2020-12-08T04:00:00+00:00
 
3
2020-12-08T00:00:00+00:00
 
3
2020-12-08T11:00:00+00:00
 
2
Other values (14)
17 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2325
Distinct characters13
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)11.8%

Sample

1st row2020-12-07T21:00:00+00:00
2nd row2020-12-08T00:00:00+00:00
3rd row2020-12-08T00:00:00+00:00
4th row2020-12-08T00:00:00+00:00
5th row2020-12-08T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-08T12:00:00+00:0063
67.7%
2020-12-08T17:00:00+00:005
 
5.4%
2020-12-08T04:00:00+00:003
 
3.2%
2020-12-08T00:00:00+00:003
 
3.2%
2020-12-08T11:00:00+00:002
 
2.2%
2020-12-08T02:00:00+00:002
 
2.2%
2020-12-08T19:40:00+00:002
 
2.2%
2020-12-08T09:00:00+00:002
 
2.2%
2020-12-08T13:30:00+00:001
 
1.1%
2020-12-08T19:00:00+00:001
 
1.1%
Other values (9)9
 
9.7%

Length

2022-09-05T21:39:39.044614image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-08t12:00:00+00:0063
67.7%
2020-12-08t17:00:00+00:005
 
5.4%
2020-12-08t04:00:00+00:003
 
3.2%
2020-12-08t00:00:00+00:003
 
3.2%
2020-12-08t11:00:00+00:002
 
2.2%
2020-12-08t02:00:00+00:002
 
2.2%
2020-12-08t19:40:00+00:002
 
2.2%
2020-12-08t09:00:00+00:002
 
2.2%
2020-12-08t13:00:00+00:001
 
1.1%
2020-12-08t03:00:00+00:001
 
1.1%
Other values (9)9
 
9.7%

Most occurring characters

ValueCountFrequency (%)
01033
44.4%
2347
 
14.9%
:279
 
12.0%
-186
 
8.0%
1173
 
7.4%
T93
 
4.0%
+93
 
4.0%
892
 
4.0%
47
 
0.3%
76
 
0.3%
Other values (3)16
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1674
72.0%
Other Punctuation279
 
12.0%
Dash Punctuation186
 
8.0%
Uppercase Letter93
 
4.0%
Math Symbol93
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01033
61.7%
2347
 
20.7%
1173
 
10.3%
892
 
5.5%
47
 
0.4%
76
 
0.4%
36
 
0.4%
95
 
0.3%
55
 
0.3%
Other Punctuation
ValueCountFrequency (%)
:279
100.0%
Dash Punctuation
ValueCountFrequency (%)
-186
100.0%
Uppercase Letter
ValueCountFrequency (%)
T93
100.0%
Math Symbol
ValueCountFrequency (%)
+93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2232
96.0%
Latin93
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01033
46.3%
2347
 
15.5%
:279
 
12.5%
-186
 
8.3%
1173
 
7.8%
+93
 
4.2%
892
 
4.1%
47
 
0.3%
76
 
0.3%
36
 
0.3%
Other values (2)10
 
0.4%
Latin
ValueCountFrequency (%)
T93
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01033
44.4%
2347
 
14.9%
:279
 
12.0%
-186
 
8.0%
1173
 
7.4%
T93
 
4.0%
+93
 
4.0%
892
 
4.0%
47
 
0.3%
76
 
0.3%
Other values (3)16
 
0.7%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)37.1%
Missing4
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean34.98876404
Minimum3
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:39.127959image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.4
Q120
median30
Q345
95-th percentile83.2
Maximum120
Range117
Interquartile range (IQR)25

Descriptive statistics

Standard deviation23.74413534
Coefficient of variation (CV)0.6786217231
Kurtosis4.098631945
Mean34.98876404
Median Absolute Deviation (MAD)15
Skewness1.687570163
Sum3114
Variance563.7839632
MonotonicityNot monotonic
2022-09-05T21:39:39.232892image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4519
20.4%
3012
 
12.9%
265
 
5.4%
124
 
4.3%
53
 
3.2%
253
 
3.2%
1203
 
3.2%
503
 
3.2%
162
 
2.2%
572
 
2.2%
Other values (23)33
35.5%
(Missing)4
 
4.3%
ValueCountFrequency (%)
31
 
1.1%
53
3.2%
61
 
1.1%
71
 
1.1%
82
2.2%
91
 
1.1%
102
2.2%
124
4.3%
132
2.2%
141
 
1.1%
ValueCountFrequency (%)
1203
 
3.2%
902
 
2.2%
731
 
1.1%
602
 
2.2%
572
 
2.2%
503
 
3.2%
4519
20.4%
431
 
1.1%
421
 
1.1%
401
 
1.1%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct29
Distinct (%)100.0%
Missing64
Missing (%)68.8%
Memory size872.0 B
<p><b>#Camping Decoration #Did You Come Sehun?</b></p>
 
1
<p>Menacée par Lola qui lui en veut d'avoir trahi Cheyenne, Rachida sort un atout de dernière minute de sa manche.</p>
 
1
<p>Le mari de Cheyenne, Joël Barden, s'est évadé de prison. Il refuse de partir en cavale sans elle avec la BRB aux trousses.</p>
 
1
<p>At age 17, Seth was living a rock star life while supplying 15 colleges in 5 different states, with massive amounts of acid and weed until the US Marshalls set their sites on him.</p>
 
1
<p>Big News calls Rudy Giuliani to wish him a speedy recovery while Pulitzer-winning journalist Clarence Page joins the show to discuss the Covid crisis and Trump's post-presidency plans. </p>
 
1
Other values (24)
24 

Length

Max length939
Median length156
Mean length184.4137931
Min length54

Characters and Unicode

Total characters5348
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)100.0%

Sample

1st row<p><b>#Camping Decoration #Did You Come Sehun?</b></p>
2nd row<p>Iron Man 2 HISHE!!! In the final battle, Ivan Vanko leaves his computer to go suit up. Black Widow then finds that computer and is able to use it to reboot War Machine. Why stop there? </p>
3rd row<p>This week Mike and the team head to The Big Easy to meet up with Max Steitz and Franziska Trautmann, who after a bottle of wine one night, found themselves frustrated by New Orleans' lack of glass recycling. One thing led to another, and Glass Half Full was born; A grassroots glass recycling program that turns glass bottles into sand and cullet for disaster relief and prevention.</p>
4th row<p>To connect or disconnect? That's the question Gabe asks when his class receives new tablet devices. Mikey tries to overcome his shyness with Marisol.</p>
5th row<p>To counter his students' pessimism about the future, Gabe makes them create vision boards of what they want in life, an assignment he takes to heart.</p>

Common Values

ValueCountFrequency (%)
<p><b>#Camping Decoration #Did You Come Sehun?</b></p>1
 
1.1%
<p>Menacée par Lola qui lui en veut d'avoir trahi Cheyenne, Rachida sort un atout de dernière minute de sa manche.</p>1
 
1.1%
<p>Le mari de Cheyenne, Joël Barden, s'est évadé de prison. Il refuse de partir en cavale sans elle avec la BRB aux trousses.</p>1
 
1.1%
<p>At age 17, Seth was living a rock star life while supplying 15 colleges in 5 different states, with massive amounts of acid and weed until the US Marshalls set their sites on him.</p>1
 
1.1%
<p>Big News calls Rudy Giuliani to wish him a speedy recovery while Pulitzer-winning journalist Clarence Page joins the show to discuss the Covid crisis and Trump's post-presidency plans. </p>1
 
1.1%
<p>Eric tries to move on, but fallout from the affair continues to resurface in unexpected ways.</p>1
 
1.1%
<p>After listening to the original song of 'No. 77', 'Yuki Ebana' was convinced that it was a song she sang for herself, and headed to the place where she used to live on the street, where she sang 'No. 77'. Discover the boy. The song 'No. 77' was made with the boy's singing in mind, Yuki.<br />Yuki tells her boy that their debut song is 'No. 77' made by the boy, and she takes the boy to meet her office president 'Yuichi Yanagishita'. The boy and Yanagishita will have a discussion together.<br />She returns and she tells the story to 'Ryo', 'Shiori Kato' and 'Hitoko Murakami'. Hitoko wonders if the boy is destined for Yuki. Ryo tells us that he wants to see you guys debut and play an active part as soon as possible, even if it's a human song.<br />However, the boy did not respond to Yanagishita's persuasion, and he refused to let him use his song. Ryo appeared to Yanagishita who was in trouble and said, 'Leave him to me.'</p>1
 
1.1%
<p>As she and Makoto begin dating, Kiki feels a bit shy at first but enjoys spending time with him. One day they run into Takumi and Riho while out on a date. Kiki feels awkward around Takumi but does her best to make conversation. Meanwhile, at work, she's suddenly told that she's being removed from the confectionary development team.</p>1
 
1.1%
<p>With the truth finally out in the open, Paul constructs a cockamamie plan to save the town with the help of an unexpected ally hidden in plain sight. </p>1
 
1.1%
<p>Day 2. Meeting up the morning after Dong seduced Vee, Dong's reaction is not what Vee expected - so Jennifer decides to interfere.</p>1
 
1.1%
Other values (19)19
 
20.4%
(Missing)64
68.8%

Length

2022-09-05T21:39:39.335158image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the51
 
5.6%
to34
 
3.7%
and33
 
3.6%
a17
 
1.9%
of13
 
1.4%
in12
 
1.3%
with9
 
1.0%
is9
 
1.0%
their8
 
0.9%
boy7
 
0.8%
Other values (503)716
78.8%

Most occurring characters

ValueCountFrequency (%)
876
16.4%
e515
 
9.6%
a355
 
6.6%
t352
 
6.6%
s301
 
5.6%
i289
 
5.4%
n285
 
5.3%
o264
 
4.9%
h207
 
3.9%
r206
 
3.9%
Other values (62)1698
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3964
74.1%
Space Separator880
 
16.5%
Other Punctuation177
 
3.3%
Uppercase Letter177
 
3.3%
Math Symbol126
 
2.4%
Decimal Number17
 
0.3%
Dash Punctuation7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e515
13.0%
a355
 
9.0%
t352
 
8.9%
s301
 
7.6%
i289
 
7.3%
n285
 
7.2%
o264
 
6.7%
h207
 
5.2%
r206
 
5.2%
l153
 
3.9%
Other values (19)1037
26.2%
Uppercase Letter
ValueCountFrequency (%)
T21
 
11.9%
M14
 
7.9%
A13
 
7.3%
H11
 
6.2%
S10
 
5.6%
Y10
 
5.6%
I10
 
5.6%
R8
 
4.5%
D8
 
4.5%
G7
 
4.0%
Other values (13)65
36.7%
Other Punctuation
ValueCountFrequency (%)
.51
28.8%
,39
22.0%
'36
20.3%
/33
18.6%
?9
 
5.1%
:3
 
1.7%
!3
 
1.7%
#2
 
1.1%
;1
 
0.6%
Decimal Number
ValueCountFrequency (%)
79
52.9%
13
 
17.6%
52
 
11.8%
22
 
11.8%
91
 
5.9%
Space Separator
ValueCountFrequency (%)
876
99.5%
 4
 
0.5%
Math Symbol
ValueCountFrequency (%)
<63
50.0%
>63
50.0%
Dash Punctuation
ValueCountFrequency (%)
-6
85.7%
1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4141
77.4%
Common1207
 
22.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e515
12.4%
a355
 
8.6%
t352
 
8.5%
s301
 
7.3%
i289
 
7.0%
n285
 
6.9%
o264
 
6.4%
h207
 
5.0%
r206
 
5.0%
l153
 
3.7%
Other values (42)1214
29.3%
Common
ValueCountFrequency (%)
876
72.6%
<63
 
5.2%
>63
 
5.2%
.51
 
4.2%
,39
 
3.2%
'36
 
3.0%
/33
 
2.7%
79
 
0.7%
?9
 
0.7%
-6
 
0.5%
Other values (10)22
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII5338
99.8%
None9
 
0.2%
Punctuation1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
876
16.4%
e515
 
9.6%
a355
 
6.7%
t352
 
6.6%
s301
 
5.6%
i289
 
5.4%
n285
 
5.3%
o264
 
4.9%
h207
 
3.9%
r206
 
3.9%
Other values (57)1688
31.6%
None
ValueCountFrequency (%)
 4
44.4%
é3
33.3%
ë1
 
11.1%
è1
 
11.1%
Punctuation
ValueCountFrequency (%)
1
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)57.1%
Missing86
Missing (%)92.5%
Memory size872.0 B
7.3
7.7
9.5
7.2

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st row7.7
2nd row7.3
3rd row7.3
4th row7.7
5th row7.3

Common Values

ValueCountFrequency (%)
7.33
 
3.2%
7.72
 
2.2%
9.51
 
1.1%
7.21
 
1.1%
(Missing)86
92.5%

Length

2022-09-05T21:39:39.421766image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:39.509202image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.33
42.9%
7.72
28.6%
9.51
 
14.3%
7.21
 
14.3%

Most occurring characters

ValueCountFrequency (%)
78
38.1%
.7
33.3%
33
 
14.3%
91
 
4.8%
51
 
4.8%
21
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number14
66.7%
Other Punctuation7
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
78
57.1%
33
 
21.4%
91
 
7.1%
51
 
7.1%
21
 
7.1%
Other Punctuation
ValueCountFrequency (%)
.7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
78
38.1%
.7
33.3%
33
 
14.3%
91
 
4.8%
51
 
4.8%
21
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
38.1%
.7
33.3%
33
 
14.3%
91
 
4.8%
51
 
4.8%
21
 
4.8%

_links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
https://api.tvmaze.com/episodes/1988857
 
1
https://api.tvmaze.com/episodes/1977636
 
1
https://api.tvmaze.com/episodes/1984946
 
1
https://api.tvmaze.com/episodes/1984945
 
1
https://api.tvmaze.com/episodes/1984944
 
1
Other values (88)
88 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3627
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988857
2nd rowhttps://api.tvmaze.com/episodes/2007748
3rd rowhttps://api.tvmaze.com/episodes/1986870
4th rowhttps://api.tvmaze.com/episodes/2008028
5th rowhttps://api.tvmaze.com/episodes/1964566

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888571
 
1.1%
https://api.tvmaze.com/episodes/19776361
 
1.1%
https://api.tvmaze.com/episodes/19849461
 
1.1%
https://api.tvmaze.com/episodes/19849451
 
1.1%
https://api.tvmaze.com/episodes/19849441
 
1.1%
https://api.tvmaze.com/episodes/19849431
 
1.1%
https://api.tvmaze.com/episodes/19849421
 
1.1%
https://api.tvmaze.com/episodes/19849411
 
1.1%
https://api.tvmaze.com/episodes/19849401
 
1.1%
https://api.tvmaze.com/episodes/21751091
 
1.1%
Other values (83)83
89.2%

Length

2022-09-05T21:39:39.583558image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888571
 
1.1%
https://api.tvmaze.com/episodes/19840301
 
1.1%
https://api.tvmaze.com/episodes/19868701
 
1.1%
https://api.tvmaze.com/episodes/20080281
 
1.1%
https://api.tvmaze.com/episodes/19645661
 
1.1%
https://api.tvmaze.com/episodes/20525071
 
1.1%
https://api.tvmaze.com/episodes/20962951
 
1.1%
https://api.tvmaze.com/episodes/19735441
 
1.1%
https://api.tvmaze.com/episodes/19735451
 
1.1%
https://api.tvmaze.com/episodes/20821731
 
1.1%
Other values (83)83
89.2%

Most occurring characters

ValueCountFrequency (%)
/372
 
10.3%
p279
 
7.7%
s279
 
7.7%
e279
 
7.7%
t279
 
7.7%
o186
 
5.1%
a186
 
5.1%
i186
 
5.1%
.186
 
5.1%
m186
 
5.1%
Other values (16)1209
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2325
64.1%
Other Punctuation651
 
17.9%
Decimal Number651
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p279
12.0%
s279
12.0%
e279
12.0%
t279
12.0%
o186
8.0%
a186
8.0%
i186
8.0%
m186
8.0%
h93
 
4.0%
d93
 
4.0%
Other values (3)279
12.0%
Decimal Number
ValueCountFrequency (%)
1109
16.7%
9103
15.8%
281
12.4%
873
11.2%
756
8.6%
056
8.6%
354
8.3%
447
7.2%
646
7.1%
526
 
4.0%
Other Punctuation
ValueCountFrequency (%)
/372
57.1%
.186
28.6%
:93
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2325
64.1%
Common1302
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/372
28.6%
.186
14.3%
1109
 
8.4%
9103
 
7.9%
:93
 
7.1%
281
 
6.2%
873
 
5.6%
756
 
4.3%
056
 
4.3%
354
 
4.1%
Other values (3)119
 
9.1%
Latin
ValueCountFrequency (%)
p279
12.0%
s279
12.0%
e279
12.0%
t279
12.0%
o186
8.0%
a186
8.0%
i186
8.0%
m186
8.0%
h93
 
4.0%
d93
 
4.0%
Other values (3)279
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3627
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/372
 
10.3%
p279
 
7.7%
s279
 
7.7%
e279
 
7.7%
t279
 
7.7%
o186
 
5.1%
a186
 
5.1%
i186
 
5.1%
.186
 
5.1%
m186
 
5.1%
Other values (16)1209
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct66
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46709.63441
Minimum2504
Maximum63761
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:39.678748image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2504
5-th percentile15250
Q142899
median50752
Q352400
95-th percentile60794.6
Maximum63761
Range61257
Interquartile range (IQR)9501

Descriptive statistics

Standard deviation12492.88333
Coefficient of variation (CV)0.2674583839
Kurtosis3.138450104
Mean46709.63441
Median Absolute Deviation (MAD)1782
Skewness-1.823603121
Sum4343996
Variance156072133.9
MonotonicityNot monotonic
2022-09-05T21:39:39.791121image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4914710
 
10.8%
524008
 
8.6%
419305
 
5.4%
521042
 
2.2%
520382
 
2.2%
521592
 
2.2%
521082
 
2.2%
521072
 
2.2%
501062
 
2.2%
152502
 
2.2%
Other values (56)56
60.2%
ValueCountFrequency (%)
25041
1.1%
64411
1.1%
133811
1.1%
133921
1.1%
152502
2.2%
176331
1.1%
179641
1.1%
262681
1.1%
306061
1.1%
320871
1.1%
ValueCountFrequency (%)
637611
1.1%
637191
1.1%
617551
1.1%
615301
1.1%
608091
1.1%
607851
1.1%
596761
1.1%
595551
1.1%
583671
1.1%
573391
1.1%

_embedded.show.url
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct66
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
https://www.tvmaze.com/shows/49147/world-war-two-week-by-week
10 
https://www.tvmaze.com/shows/52400/dream-detective
https://www.tvmaze.com/shows/41930/mr-iglesias
 
5
https://www.tvmaze.com/shows/52104/twisted-fate-of-love
 
2
https://www.tvmaze.com/shows/52038/please-wait-brother
 
2
Other values (61)
66 

Length

Max length71
Median length58
Mean length51.60215054
Min length40

Characters and Unicode

Total characters4799
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)60.2%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/51065/stand-up-autsajd
3rd rowhttps://www.tvmaze.com/shows/52198/kotiki
4th rowhttps://www.tvmaze.com/shows/52933/lab-s-antonom-belaevym
5th rowhttps://www.tvmaze.com/shows/51336/core-sense

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/49147/world-war-two-week-by-week10
 
10.8%
https://www.tvmaze.com/shows/52400/dream-detective8
 
8.6%
https://www.tvmaze.com/shows/41930/mr-iglesias5
 
5.4%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.2%
https://www.tvmaze.com/shows/52038/please-wait-brother2
 
2.2%
https://www.tvmaze.com/shows/52159/to-love2
 
2.2%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
2.2%
https://www.tvmaze.com/shows/52107/new-face2
 
2.2%
https://www.tvmaze.com/shows/50106/cheyenne-et-lola2
 
2.2%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.2%
Other values (56)56
60.2%

Length

2022-09-05T21:39:39.902872image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/49147/world-war-two-week-by-week10
 
10.8%
https://www.tvmaze.com/shows/52400/dream-detective8
 
8.6%
https://www.tvmaze.com/shows/41930/mr-iglesias5
 
5.4%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.2%
https://www.tvmaze.com/shows/52038/please-wait-brother2
 
2.2%
https://www.tvmaze.com/shows/52159/to-love2
 
2.2%
https://www.tvmaze.com/shows/52108/psych-hunter2
 
2.2%
https://www.tvmaze.com/shows/52107/new-face2
 
2.2%
https://www.tvmaze.com/shows/50106/cheyenne-et-lola2
 
2.2%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.2%
Other values (56)56
60.2%

Most occurring characters

ValueCountFrequency (%)
/465
 
9.7%
w444
 
9.3%
t377
 
7.9%
s355
 
7.4%
o286
 
6.0%
e275
 
5.7%
h226
 
4.7%
m223
 
4.6%
a207
 
4.3%
-190
 
4.0%
Other values (29)1751
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3398
70.8%
Other Punctuation744
 
15.5%
Decimal Number467
 
9.7%
Dash Punctuation190
 
4.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w444
13.1%
t377
11.1%
s355
10.4%
o286
 
8.4%
e275
 
8.1%
h226
 
6.7%
m223
 
6.6%
a207
 
6.1%
c130
 
3.8%
v119
 
3.5%
Other values (15)756
22.2%
Decimal Number
ValueCountFrequency (%)
467
14.3%
566
14.1%
165
13.9%
059
12.6%
245
9.6%
342
9.0%
940
8.6%
631
6.6%
727
5.8%
825
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/465
62.5%
.186
 
25.0%
:93
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-190
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3398
70.8%
Common1401
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w444
13.1%
t377
11.1%
s355
10.4%
o286
 
8.4%
e275
 
8.1%
h226
 
6.7%
m223
 
6.6%
a207
 
6.1%
c130
 
3.8%
v119
 
3.5%
Other values (15)756
22.2%
Common
ValueCountFrequency (%)
/465
33.2%
-190
13.6%
.186
 
13.3%
:93
 
6.6%
467
 
4.8%
566
 
4.7%
165
 
4.6%
059
 
4.2%
245
 
3.2%
342
 
3.0%
Other values (4)123
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII4799
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/465
 
9.7%
w444
 
9.3%
t377
 
7.9%
s355
 
7.4%
o286
 
6.0%
e275
 
5.7%
h226
 
4.7%
m223
 
4.6%
a207
 
4.3%
-190
 
4.0%
Other values (29)1751
36.5%

_embedded.show.name
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct66
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
World War Two: Week by Week
10 
Dream Detective
Mr. Iglesias
 
5
Twisted Fate of Love
 
2
Please Wait, Brother
 
2
Other values (61)
66 

Length

Max length36
Median length27
Mean length16.91397849
Min length5

Characters and Unicode

Total characters1573
Distinct characters89
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)60.2%

Sample

1st rowSim for You
2nd rowStand Up Аутсайд
3rd rowКотики
4th rowLAB с Антоном Беляевым
5th rowCore Sense

Common Values

ValueCountFrequency (%)
World War Two: Week by Week10
 
10.8%
Dream Detective8
 
8.6%
Mr. Iglesias5
 
5.4%
Twisted Fate of Love2
 
2.2%
Please Wait, Brother2
 
2.2%
To Love2
 
2.2%
Psych Hunter2
 
2.2%
New Face2
 
2.2%
Cheyenne et Lola2
 
2.2%
The Young Turks2
 
2.2%
Other values (56)56
60.2%

Length

2022-09-05T21:39:40.013253image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
week20
 
7.0%
world10
 
3.5%
two10
 
3.5%
by10
 
3.5%
war10
 
3.5%
dream8
 
2.8%
detective8
 
2.8%
mr5
 
1.8%
iglesias5
 
1.8%
the5
 
1.8%
Other values (162)193
68.0%

Most occurring characters

ValueCountFrequency (%)
191
 
12.1%
e173
 
11.0%
a93
 
5.9%
o86
 
5.5%
r78
 
5.0%
i69
 
4.4%
t64
 
4.1%
n59
 
3.8%
s54
 
3.4%
l51
 
3.2%
Other values (79)655
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1095
69.6%
Uppercase Letter257
 
16.3%
Space Separator191
 
12.1%
Other Punctuation26
 
1.7%
Decimal Number4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e173
15.8%
a93
 
8.5%
o86
 
7.9%
r78
 
7.1%
i69
 
6.3%
t64
 
5.8%
n59
 
5.4%
s54
 
4.9%
l51
 
4.7%
d35
 
3.2%
Other values (39)333
30.4%
Uppercase Letter
ValueCountFrequency (%)
W49
19.1%
T31
12.1%
D22
 
8.6%
S16
 
6.2%
A13
 
5.1%
M13
 
5.1%
F11
 
4.3%
B10
 
3.9%
C9
 
3.5%
N9
 
3.5%
Other values (19)74
28.8%
Other Punctuation
ValueCountFrequency (%)
:11
42.3%
.6
23.1%
,3
 
11.5%
'3
 
11.5%
!1
 
3.8%
&1
 
3.8%
?1
 
3.8%
Decimal Number
ValueCountFrequency (%)
02
50.0%
11
25.0%
21
25.0%
Space Separator
ValueCountFrequency (%)
191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1283
81.6%
Common221
 
14.0%
Cyrillic69
 
4.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e173
 
13.5%
a93
 
7.2%
o86
 
6.7%
r78
 
6.1%
i69
 
5.4%
t64
 
5.0%
n59
 
4.6%
s54
 
4.2%
l51
 
4.0%
W49
 
3.8%
Other values (40)507
39.5%
Cyrillic
ValueCountFrequency (%)
о9
 
13.0%
е5
 
7.2%
п4
 
5.8%
с4
 
5.8%
р4
 
5.8%
и3
 
4.3%
л3
 
4.3%
я3
 
4.3%
в3
 
4.3%
а3
 
4.3%
Other values (18)28
40.6%
Common
ValueCountFrequency (%)
191
86.4%
:11
 
5.0%
.6
 
2.7%
,3
 
1.4%
'3
 
1.4%
02
 
0.9%
!1
 
0.5%
&1
 
0.5%
11
 
0.5%
21
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1499
95.3%
Cyrillic69
 
4.4%
None5
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191
 
12.7%
e173
 
11.5%
a93
 
6.2%
o86
 
5.7%
r78
 
5.2%
i69
 
4.6%
t64
 
4.3%
n59
 
3.9%
s54
 
3.6%
l51
 
3.4%
Other values (48)581
38.8%
Cyrillic
ValueCountFrequency (%)
о9
 
13.0%
е5
 
7.2%
п4
 
5.8%
с4
 
5.8%
р4
 
5.8%
и3
 
4.3%
л3
 
4.3%
я3
 
4.3%
в3
 
4.3%
а3
 
4.3%
Other values (18)28
40.6%
None
ValueCountFrequency (%)
ø3
60.0%
ş1
 
20.0%
ı1
 
20.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size872.0 B
Scripted
44 
Documentary
17 
Talk Show
Animation
Reality
Other values (4)
12 

Length

Max length11
Median length9
Mean length8.397849462
Min length4

Characters and Unicode

Total characters781
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowReality
2nd rowVariety
3rd rowScripted
4th rowDocumentary
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted44
47.3%
Documentary17
 
18.3%
Talk Show9
 
9.7%
Animation6
 
6.5%
Reality5
 
5.4%
Sports5
 
5.4%
Variety3
 
3.2%
News3
 
3.2%
Game Show1
 
1.1%

Length

2022-09-05T21:39:40.109913image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:40.207683image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted44
42.7%
documentary17
 
16.5%
show10
 
9.7%
talk9
 
8.7%
animation6
 
5.8%
reality5
 
4.9%
sports5
 
4.9%
variety3
 
2.9%
news3
 
2.9%
game1
 
1.0%

Most occurring characters

ValueCountFrequency (%)
t80
 
10.2%
e73
 
9.3%
r69
 
8.8%
i64
 
8.2%
c61
 
7.8%
S59
 
7.6%
p49
 
6.3%
d44
 
5.6%
a41
 
5.2%
o38
 
4.9%
Other values (17)203
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter668
85.5%
Uppercase Letter103
 
13.2%
Space Separator10
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t80
12.0%
e73
10.9%
r69
10.3%
i64
9.6%
c61
9.1%
p49
7.3%
d44
 
6.6%
a41
 
6.1%
o38
 
5.7%
n29
 
4.3%
Other values (8)120
18.0%
Uppercase Letter
ValueCountFrequency (%)
S59
57.3%
D17
 
16.5%
T9
 
8.7%
A6
 
5.8%
R5
 
4.9%
V3
 
2.9%
N3
 
2.9%
G1
 
1.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin771
98.7%
Common10
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t80
10.4%
e73
 
9.5%
r69
 
8.9%
i64
 
8.3%
c61
 
7.9%
S59
 
7.7%
p49
 
6.4%
d44
 
5.7%
a41
 
5.3%
o38
 
4.9%
Other values (16)193
25.0%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII781
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t80
 
10.2%
e73
 
9.3%
r69
 
8.8%
i64
 
8.2%
c61
 
7.8%
S59
 
7.6%
p49
 
6.3%
d44
 
5.6%
a41
 
5.2%
o38
 
4.9%
Other values (17)203
26.0%

_embedded.show.language
Categorical

HIGH CORRELATION
MISSING

Distinct13
Distinct (%)14.1%
Missing1
Missing (%)1.1%
Memory size872.0 B
English
42 
Chinese
23 
Russian
Norwegian
 
4
Korean
 
3
Other values (8)
12 

Length

Max length10
Median length7
Mean length7.043478261
Min length5

Characters and Unicode

Total characters648
Distinct characters28
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)4.3%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowChinese

Common Values

ValueCountFrequency (%)
English42
45.2%
Chinese23
24.7%
Russian8
 
8.6%
Norwegian4
 
4.3%
Korean3
 
3.2%
Turkish2
 
2.2%
Arabic2
 
2.2%
Japanese2
 
2.2%
French2
 
2.2%
Persian1
 
1.1%
Other values (3)3
 
3.2%

Length

2022-09-05T21:39:40.299115image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english42
45.7%
chinese23
25.0%
russian8
 
8.7%
norwegian4
 
4.3%
korean3
 
3.3%
turkish2
 
2.2%
arabic2
 
2.2%
japanese2
 
2.2%
french2
 
2.2%
persian1
 
1.1%
Other values (3)3
 
3.3%

Most occurring characters

ValueCountFrequency (%)
s87
13.4%
n85
13.1%
i82
12.7%
h70
10.8%
e62
9.6%
g49
7.6%
l43
6.6%
E42
6.5%
a24
 
3.7%
C23
 
3.5%
Other values (18)81
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter556
85.8%
Uppercase Letter92
 
14.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s87
15.6%
n85
15.3%
i82
14.7%
h70
12.6%
e62
11.2%
g49
8.8%
l43
7.7%
a24
 
4.3%
r15
 
2.7%
u13
 
2.3%
Other values (7)26
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
E42
45.7%
C23
25.0%
R8
 
8.7%
N4
 
4.3%
K3
 
3.3%
T3
 
3.3%
P2
 
2.2%
F2
 
2.2%
A2
 
2.2%
J2
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Latin648
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s87
13.4%
n85
13.1%
i82
12.7%
h70
10.8%
e62
9.6%
g49
7.6%
l43
6.6%
E42
6.5%
a24
 
3.7%
C23
 
3.5%
Other values (18)81
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII648
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s87
13.4%
n85
13.1%
i82
12.7%
h70
10.8%
e62
9.6%
g49
7.6%
l43
6.6%
E42
6.5%
a24
 
3.7%
C23
 
3.5%
Other values (18)81
12.5%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size872.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size872.0 B
Running
52 
Ended
37 
To Be Determined
 
4

Length

Max length16
Median length7
Mean length6.591397849
Min length5

Characters and Unicode

Total characters613
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowEnded
3rd rowEnded
4th rowTo Be Determined
5th rowRunning

Common Values

ValueCountFrequency (%)
Running52
55.9%
Ended37
39.8%
To Be Determined4
 
4.3%

Length

2022-09-05T21:39:40.382755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:40.461318image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running52
51.5%
ended37
36.6%
to4
 
4.0%
be4
 
4.0%
determined4
 
4.0%

Most occurring characters

ValueCountFrequency (%)
n197
32.1%
d78
 
12.7%
i56
 
9.1%
e53
 
8.6%
R52
 
8.5%
u52
 
8.5%
g52
 
8.5%
E37
 
6.0%
8
 
1.3%
T4
 
0.7%
Other values (6)24
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter504
82.2%
Uppercase Letter101
 
16.5%
Space Separator8
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n197
39.1%
d78
 
15.5%
i56
 
11.1%
e53
 
10.5%
u52
 
10.3%
g52
 
10.3%
o4
 
0.8%
t4
 
0.8%
r4
 
0.8%
m4
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
R52
51.5%
E37
36.6%
T4
 
4.0%
B4
 
4.0%
D4
 
4.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin605
98.7%
Common8
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n197
32.6%
d78
 
12.9%
i56
 
9.3%
e53
 
8.8%
R52
 
8.6%
u52
 
8.6%
g52
 
8.6%
E37
 
6.1%
T4
 
0.7%
o4
 
0.7%
Other values (5)20
 
3.3%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII613
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n197
32.1%
d78
 
12.7%
i56
 
9.1%
e53
 
8.6%
R52
 
8.5%
u52
 
8.5%
g52
 
8.5%
E37
 
6.0%
8
 
1.3%
T4
 
0.7%
Other values (6)24
 
3.9%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)33.8%
Missing19
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean37.59459459
Minimum3
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:40.534979image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile6.95
Q120
median32.5
Q345
95-th percentile100.5
Maximum180
Range177
Interquartile range (IQR)25

Descriptive statistics

Standard deviation29.17679643
Coefficient of variation (CV)0.7760901998
Kurtosis8.529447145
Mean37.59459459
Median Absolute Deviation (MAD)12.5
Skewness2.485424566
Sum2782
Variance851.2854498
MonotonicityNot monotonic
2022-09-05T21:39:40.624809image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4519
20.4%
2013
14.0%
503
 
3.2%
1203
 
3.2%
53
 
3.2%
403
 
3.2%
253
 
3.2%
303
 
3.2%
123
 
3.2%
372
 
2.2%
Other values (15)19
20.4%
(Missing)19
20.4%
ValueCountFrequency (%)
31
 
1.1%
53
 
3.2%
81
 
1.1%
101
 
1.1%
123
 
3.2%
141
 
1.1%
152
 
2.2%
161
 
1.1%
2013
14.0%
231
 
1.1%
ValueCountFrequency (%)
1801
 
1.1%
1203
 
3.2%
901
 
1.1%
602
 
2.2%
572
 
2.2%
503
 
3.2%
4519
20.4%
403
 
3.2%
372
 
2.2%
351
 
1.1%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct33
Distinct (%)36.3%
Missing2
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean33.56043956
Minimum3
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:40.713838image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7
Q115
median28
Q345
95-th percentile88.5
Maximum120
Range117
Interquartile range (IQR)30

Descriptive statistics

Standard deviation24.53397136
Coefficient of variation (CV)0.7310384395
Kurtosis3.669265718
Mean33.56043956
Median Absolute Deviation (MAD)16
Skewness1.705347922
Sum3054
Variance601.9157509
MonotonicityNot monotonic
2022-09-05T21:39:40.817344image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
4518
19.4%
1510
 
10.8%
295
 
5.4%
125
 
5.4%
255
 
5.4%
144
 
4.3%
1203
 
3.2%
373
 
3.2%
503
 
3.2%
53
 
3.2%
Other values (23)32
34.4%
ValueCountFrequency (%)
31
 
1.1%
53
3.2%
61
 
1.1%
81
 
1.1%
91
 
1.1%
101
 
1.1%
111
 
1.1%
125
5.4%
131
 
1.1%
144
4.3%
ValueCountFrequency (%)
1203
 
3.2%
902
 
2.2%
871
 
1.1%
602
 
2.2%
591
 
1.1%
571
 
1.1%
561
 
1.1%
503
 
3.2%
4518
19.4%
402
 
2.2%

_embedded.show.premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct53
Distinct (%)57.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
2018-09-01
10 
2020-12-08
2020-11-24
2020-11-23
 
5
2019-06-21
 
5
Other values (48)
58 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters930
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)44.1%

Sample

1st row2019-03-25
2nd row2020-10-13
3rd row2020-11-30
4th row2019-12-17
5th row2020-10-13

Common Values

ValueCountFrequency (%)
2018-09-0110
 
10.8%
2020-12-089
 
9.7%
2020-11-246
 
6.5%
2020-11-235
 
5.4%
2019-06-215
 
5.4%
2020-10-133
 
3.2%
2020-11-173
 
3.2%
2020-12-013
 
3.2%
2020-11-192
 
2.2%
2020-10-202
 
2.2%
Other values (43)45
48.4%

Length

2022-09-05T21:39:40.902645image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-09-0110
 
10.8%
2020-12-089
 
9.7%
2020-11-246
 
6.5%
2020-11-235
 
5.4%
2019-06-215
 
5.4%
2020-10-133
 
3.2%
2020-11-173
 
3.2%
2020-12-013
 
3.2%
2020-11-302
 
2.2%
2013-12-242
 
2.2%
Other values (43)45
48.4%

Most occurring characters

ValueCountFrequency (%)
0242
26.0%
2191
20.5%
-186
20.0%
1157
16.9%
945
 
4.8%
835
 
3.8%
326
 
2.8%
716
 
1.7%
413
 
1.4%
510
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number744
80.0%
Dash Punctuation186
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0242
32.5%
2191
25.7%
1157
21.1%
945
 
6.0%
835
 
4.7%
326
 
3.5%
716
 
2.2%
413
 
1.7%
510
 
1.3%
69
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
-186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common930
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0242
26.0%
2191
20.5%
-186
20.0%
1157
16.9%
945
 
4.8%
835
 
3.8%
326
 
2.8%
716
 
1.7%
413
 
1.4%
510
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII930
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0242
26.0%
2191
20.5%
-186
20.0%
1157
16.9%
945
 
4.8%
835
 
3.8%
326
 
2.8%
716
 
1.7%
413
 
1.4%
510
 
1.1%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct17
Distinct (%)45.9%
Missing56
Missing (%)60.2%
Memory size872.0 B
2021-01-05
2020-12-08
2020-12-22
2020-12-30
2020-12-23
Other values (12)
14 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters370
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)27.0%

Sample

1st row2020-12-31
2nd row2020-12-11
3rd row2021-01-06
4th row2020-12-08
5th row2020-12-08

Common Values

ValueCountFrequency (%)
2021-01-058
 
8.6%
2020-12-087
 
7.5%
2020-12-224
 
4.3%
2020-12-302
 
2.2%
2020-12-232
 
2.2%
2020-12-162
 
2.2%
2020-12-152
 
2.2%
2020-12-041
 
1.1%
2021-11-281
 
1.1%
2020-12-141
 
1.1%
Other values (7)7
 
7.5%
(Missing)56
60.2%

Length

2022-09-05T21:39:40.981210image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01-058
21.6%
2020-12-087
18.9%
2020-12-224
10.8%
2020-12-302
 
5.4%
2020-12-232
 
5.4%
2020-12-162
 
5.4%
2020-12-152
 
5.4%
2021-11-111
 
2.7%
2020-12-111
 
2.7%
2021-01-061
 
2.7%
Other values (7)7
18.9%

Most occurring characters

ValueCountFrequency (%)
2113
30.5%
092
24.9%
-74
20.0%
161
16.5%
510
 
2.7%
88
 
2.2%
35
 
1.4%
63
 
0.8%
43
 
0.8%
91
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number296
80.0%
Dash Punctuation74
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2113
38.2%
092
31.1%
161
20.6%
510
 
3.4%
88
 
2.7%
35
 
1.7%
63
 
1.0%
43
 
1.0%
91
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common370
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2113
30.5%
092
24.9%
-74
20.0%
161
16.5%
510
 
2.7%
88
 
2.2%
35
 
1.4%
63
 
0.8%
43
 
0.8%
91
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII370
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2113
30.5%
092
24.9%
-74
20.0%
161
16.5%
510
 
2.7%
88
 
2.2%
35
 
1.4%
63
 
0.8%
43
 
0.8%
91
 
0.3%

_embedded.show.officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct58
Distinct (%)69.0%
Missing9
Missing (%)9.7%
Memory size872.0 B
https://www.youtube.com/c/WorldWarTwo/playlists?view=50&sort=dd&shelf_id=5
10 
https://v.qq.com/detail/m/mzc00200ur8p8zp.html
https://www.netflix.com/title/80209013
 
5
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=1
 
2
https://www.tytnetwork.com
 
2
Other values (53)
57 

Length

Max length97
Median length72
Mean length52.95238095
Min length18

Characters and Unicode

Total characters4448
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)58.3%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://premier.one/show/13734
3rd rowhttp://epic-media.ru/project/kotiki
4th rowhttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva
5th rowhttps://www.bilibili.com/bangumi/media/md28223064

Common Values

ValueCountFrequency (%)
https://www.youtube.com/c/WorldWarTwo/playlists?view=50&sort=dd&shelf_id=510
 
10.8%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html8
 
8.6%
https://www.netflix.com/title/802090135
 
5.4%
https://so.youku.com/search_video/q_%20%E6%9C%80%E5%88%9D%E7%9A%84%E7%9B%B8%E9%81%87?searchfrom=12
 
2.2%
https://www.tytnetwork.com2
 
2.2%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.2%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.2%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.2%
https://go.ocs.fr/details/serie/PSCHEYENNEEW01682592
 
2.2%
https://www.mpt.org/programs/farm/1
 
1.1%
Other values (48)48
51.6%
(Missing)9
 
9.7%

Length

2022-09-05T21:39:41.087527image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.youtube.com/c/worldwartwo/playlists?view=50&sort=dd&shelf_id=510
 
11.9%
https://v.qq.com/detail/m/mzc00200ur8p8zp.html8
 
9.5%
https://www.netflix.com/title/802090135
 
6.0%
https://so.youku.com/search_video/q_%20%e6%9c%80%e5%88%9d%e7%9a%84%e7%9b%b8%e9%81%87?searchfrom=12
 
2.4%
https://www.tytnetwork.com2
 
2.4%
https://www.iqiyi.com/a_19rrhskr95.html2
 
2.4%
https://v.qq.com/detail/m/mzc00200tu76tos.html2
 
2.4%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.4%
https://go.ocs.fr/details/serie/pscheyenneew01682592
 
2.4%
http://tv3.ru/project/slepaya1
 
1.2%
Other values (48)48
57.1%

Most occurring characters

ValueCountFrequency (%)
/361
 
8.1%
t354
 
8.0%
s228
 
5.1%
o222
 
5.0%
w193
 
4.3%
e188
 
4.2%
.176
 
4.0%
i155
 
3.5%
l152
 
3.4%
p148
 
3.3%
Other values (64)2271
51.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2932
65.9%
Other Punctuation729
 
16.4%
Decimal Number378
 
8.5%
Uppercase Letter282
 
6.3%
Math Symbol51
 
1.1%
Dash Punctuation50
 
1.1%
Connector Punctuation26
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t354
 
12.1%
s228
 
7.8%
o222
 
7.6%
w193
 
6.6%
e188
 
6.4%
i155
 
5.3%
l152
 
5.2%
p148
 
5.0%
h145
 
4.9%
m136
 
4.6%
Other values (16)1011
34.5%
Uppercase Letter
ValueCountFrequency (%)
E31
 
11.0%
W31
 
11.0%
T19
 
6.7%
A19
 
6.7%
N18
 
6.4%
P17
 
6.0%
L14
 
5.0%
C14
 
5.0%
F13
 
4.6%
B12
 
4.3%
Other values (16)94
33.3%
Decimal Number
ValueCountFrequency (%)
085
22.5%
850
13.2%
543
11.4%
240
10.6%
934
 
9.0%
129
 
7.7%
426
 
6.9%
325
 
6.6%
624
 
6.3%
722
 
5.8%
Other Punctuation
ValueCountFrequency (%)
/361
49.5%
.176
24.1%
:84
 
11.5%
%57
 
7.8%
&25
 
3.4%
?24
 
3.3%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=49
96.1%
+2
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
-50
100.0%
Connector Punctuation
ValueCountFrequency (%)
_26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3214
72.3%
Common1234
 
27.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t354
 
11.0%
s228
 
7.1%
o222
 
6.9%
w193
 
6.0%
e188
 
5.8%
i155
 
4.8%
l152
 
4.7%
p148
 
4.6%
h145
 
4.5%
m136
 
4.2%
Other values (42)1293
40.2%
Common
ValueCountFrequency (%)
/361
29.3%
.176
14.3%
085
 
6.9%
:84
 
6.8%
%57
 
4.6%
-50
 
4.1%
850
 
4.1%
=49
 
4.0%
543
 
3.5%
240
 
3.2%
Other values (12)239
19.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII4448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/361
 
8.1%
t354
 
8.0%
s228
 
5.1%
o222
 
5.0%
w193
 
4.3%
e188
 
4.2%
.176
 
4.0%
i155
 
3.5%
l152
 
3.4%
p148
 
3.3%
Other values (64)2271
51.1%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct15
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size872.0 B
61 
20:00
15 
10:00
 
3
12:00
 
2
20:40
 
2
Other values (10)
10 

Length

Max length5
Median length0
Mean length1.720430108
Min length0

Characters and Unicode

Total characters160
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)10.8%

Sample

1st row
2nd row
3rd row10:00
4th row23:45
5th row10:00

Common Values

ValueCountFrequency (%)
61
65.6%
20:0015
 
16.1%
10:003
 
3.2%
12:002
 
2.2%
20:402
 
2.2%
23:451
 
1.1%
08:001
 
1.1%
06:001
 
1.1%
17:351
 
1.1%
19:001
 
1.1%
Other values (5)5
 
5.4%

Length

2022-09-05T21:39:41.182841image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20:0015
46.9%
10:003
 
9.4%
12:002
 
6.2%
20:402
 
6.2%
23:451
 
3.1%
08:001
 
3.1%
06:001
 
3.1%
17:351
 
3.1%
19:001
 
3.1%
07:001
 
3.1%
Other values (4)4
 
12.5%

Most occurring characters

ValueCountFrequency (%)
081
50.6%
:32
 
20.0%
223
 
14.4%
18
 
5.0%
54
 
2.5%
43
 
1.9%
33
 
1.9%
82
 
1.2%
72
 
1.2%
61
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number128
80.0%
Other Punctuation32
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
081
63.3%
223
 
18.0%
18
 
6.2%
54
 
3.1%
43
 
2.3%
33
 
2.3%
82
 
1.6%
72
 
1.6%
61
 
0.8%
91
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
081
50.6%
:32
 
20.0%
223
 
14.4%
18
 
5.0%
54
 
2.5%
43
 
1.9%
33
 
1.9%
82
 
1.2%
72
 
1.2%
61
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
081
50.6%
:32
 
20.0%
223
 
14.4%
18
 
5.0%
54
 
2.5%
43
 
1.9%
33
 
1.9%
82
 
1.2%
72
 
1.2%
61
 
0.6%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size872.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3
Distinct (%)42.9%
Missing86
Missing (%)92.5%
Memory size872.0 B
6.6
5.8
5.6

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st row6.6
2nd row6.6
3rd row6.6
4th row6.6
5th row6.6

Common Values

ValueCountFrequency (%)
6.65
 
5.4%
5.81
 
1.1%
5.61
 
1.1%
(Missing)86
92.5%

Length

2022-09-05T21:39:41.263513image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:41.347534image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
6.65
71.4%
5.81
 
14.3%
5.61
 
14.3%

Most occurring characters

ValueCountFrequency (%)
611
52.4%
.7
33.3%
52
 
9.5%
81
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number14
66.7%
Other Punctuation7
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
611
78.6%
52
 
14.3%
81
 
7.1%
Other Punctuation
ValueCountFrequency (%)
.7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
611
52.4%
.7
33.3%
52
 
9.5%
81
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
611
52.4%
.7
33.3%
52
 
9.5%
81
 
4.8%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.95698925
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:41.434713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.6
Q121
median29
Q360
95-th percentile86
Maximum94
Range93
Interquartile range (IQR)39

Descriptive statistics

Standard deviation26.13007345
Coefficient of variation (CV)0.6884127
Kurtosis-0.839713097
Mean37.95698925
Median Absolute Deviation (MAD)12
Skewness0.6774648824
Sum3530
Variance682.7807387
MonotonicityNot monotonic
2022-09-05T21:39:41.541123image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
2114
 
15.1%
7411
 
11.8%
865
 
5.4%
323
 
3.2%
243
 
3.2%
333
 
3.2%
413
 
3.2%
73
 
3.2%
273
 
3.2%
153
 
3.2%
Other values (33)42
45.2%
ValueCountFrequency (%)
12
2.2%
31
 
1.1%
42
2.2%
51
 
1.1%
73
3.2%
81
 
1.1%
111
 
1.1%
121
 
1.1%
131
 
1.1%
142
2.2%
ValueCountFrequency (%)
941
 
1.1%
871
 
1.1%
865
5.4%
831
 
1.1%
821
 
1.1%
801
 
1.1%
7411
11.8%
691
 
1.1%
631
 
1.1%
601
 
1.1%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct29
Distinct (%)33.0%
Missing5
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean110.6704545
Minimum1
Maximum516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:41.631551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.35
Q121
median67
Q3118
95-th percentile406.35
Maximum516
Range515
Interquartile range (IQR)97

Descriptive statistics

Standard deviation132.3381876
Coefficient of variation (CV)1.195786067
Kurtosis1.94891994
Mean110.6704545
Median Absolute Deviation (MAD)46
Skewness1.669101966
Sum9739
Variance17513.3959
MonotonicityNot monotonic
2022-09-05T21:39:41.729916image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2134
36.6%
10416
17.2%
15
 
5.4%
673
 
3.2%
3792
 
2.2%
302
 
2.2%
2022
 
2.2%
3272
 
2.2%
1182
 
2.2%
5161
 
1.1%
Other values (19)19
20.4%
(Missing)5
 
5.4%
ValueCountFrequency (%)
15
 
5.4%
21
 
1.1%
2134
36.6%
302
 
2.2%
511
 
1.1%
673
 
3.2%
991
 
1.1%
1021
 
1.1%
10416
17.2%
1071
 
1.1%
ValueCountFrequency (%)
5161
1.1%
5101
1.1%
5071
1.1%
4391
1.1%
4201
1.1%
3811
1.1%
3792
2.2%
3272
2.2%
3191
1.1%
3111
1.1%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct29
Distinct (%)33.0%
Missing5
Missing (%)5.4%
Memory size872.0 B
YouTube
34 
Tencent QQ
16 
Netflix
iQIYI
 
3
Shahid
 
2
Other values (24)
28 

Length

Max length14
Median length12
Mean length7.647727273
Min length3

Characters and Unicode

Total characters673
Distinct characters53
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)22.7%

Sample

1st rowV LIVE
2nd rowYouTube
3rd rowEpic Media
4th rowКиноПоиск HD
5th rowBilibili

Common Values

ValueCountFrequency (%)
YouTube34
36.6%
Tencent QQ16
17.2%
Netflix5
 
5.4%
iQIYI3
 
3.2%
Shahid2
 
2.2%
Naver TVCast2
 
2.2%
Facebook Watch2
 
2.2%
TV 2 Play2
 
2.2%
Youku2
 
2.2%
Tastemade1
 
1.1%
Other values (19)19
20.4%
(Missing)5
 
5.4%

Length

2022-09-05T21:39:41.824437image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube34
29.3%
qq16
13.8%
tencent16
13.8%
netflix5
 
4.3%
iqiyi3
 
2.6%
tv3
 
2.6%
watch2
 
1.7%
youku2
 
1.7%
22
 
1.7%
play2
 
1.7%
Other values (27)31
26.7%

Most occurring characters

ValueCountFrequency (%)
e82
12.2%
u79
 
11.7%
T59
 
8.8%
o47
 
7.0%
Y39
 
5.8%
b39
 
5.8%
Q35
 
5.2%
n34
 
5.1%
t32
 
4.8%
28
 
4.2%
Other values (43)199
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter448
66.6%
Uppercase Letter193
28.7%
Space Separator28
 
4.2%
Math Symbol2
 
0.3%
Decimal Number2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e82
18.3%
u79
17.6%
o47
10.5%
b39
8.7%
n34
7.6%
t32
 
7.1%
c22
 
4.9%
i21
 
4.7%
a19
 
4.2%
l14
 
3.1%
Other values (17)59
13.2%
Uppercase Letter
ValueCountFrequency (%)
T59
30.6%
Y39
20.2%
Q35
18.1%
V9
 
4.7%
N8
 
4.1%
I7
 
3.6%
B4
 
2.1%
P4
 
2.1%
F4
 
2.1%
S3
 
1.6%
Other values (13)21
 
10.9%
Space Separator
ValueCountFrequency (%)
28
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin632
93.9%
Common32
 
4.8%
Cyrillic9
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e82
13.0%
u79
12.5%
T59
 
9.3%
o47
 
7.4%
Y39
 
6.2%
b39
 
6.2%
Q35
 
5.5%
n34
 
5.4%
t32
 
5.1%
c22
 
3.5%
Other values (33)164
25.9%
Cyrillic
ValueCountFrequency (%)
и2
22.2%
о2
22.2%
к1
11.1%
с1
11.1%
П1
11.1%
н1
11.1%
К1
11.1%
Common
ValueCountFrequency (%)
28
87.5%
+2
 
6.2%
22
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII664
98.7%
Cyrillic9
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e82
12.3%
u79
11.9%
T59
 
8.9%
o47
 
7.1%
Y39
 
5.9%
b39
 
5.9%
Q35
 
5.3%
n34
 
5.1%
t32
 
4.8%
28
 
4.2%
Other values (36)190
28.6%
Cyrillic
ValueCountFrequency (%)
и2
22.2%
о2
22.2%
к1
11.1%
с1
11.1%
П1
11.1%
н1
11.1%
К1
11.1%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)23.7%
Missing55
Missing (%)59.1%
Memory size872.0 B
China
19 
United States
Korea, Republic of
Russian Federation
Norway
Other values (4)

Length

Max length25
Median length5
Mean length8.789473684
Min length5

Characters and Unicode

Total characters334
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)7.9%

Sample

1st rowKorea, Republic of
2nd rowRussian Federation
3rd rowRussian Federation
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China19
 
20.4%
United States5
 
5.4%
Korea, Republic of3
 
3.2%
Russian Federation3
 
3.2%
Norway3
 
3.2%
Turkey2
 
2.2%
Iran, Islamic Republic of1
 
1.1%
Brazil1
 
1.1%
Japan1
 
1.1%
(Missing)55
59.1%

Length

2022-09-05T21:39:41.917577image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:42.022140image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china19
34.5%
united5
 
9.1%
states5
 
9.1%
republic4
 
7.3%
of4
 
7.3%
korea3
 
5.5%
russian3
 
5.5%
federation3
 
5.5%
norway3
 
5.5%
turkey2
 
3.6%
Other values (4)4
 
7.3%

Most occurring characters

ValueCountFrequency (%)
a41
12.3%
i36
 
10.8%
n32
 
9.6%
e25
 
7.5%
C19
 
5.7%
h19
 
5.7%
t18
 
5.4%
17
 
5.1%
o13
 
3.9%
r13
 
3.9%
Other values (24)101
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter262
78.4%
Uppercase Letter51
 
15.3%
Space Separator17
 
5.1%
Other Punctuation4
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a41
15.6%
i36
13.7%
n32
12.2%
e25
9.5%
h19
7.3%
t18
6.9%
o13
 
5.0%
r13
 
5.0%
s12
 
4.6%
u9
 
3.4%
Other values (11)44
16.8%
Uppercase Letter
ValueCountFrequency (%)
C19
37.3%
R7
 
13.7%
S5
 
9.8%
U5
 
9.8%
K3
 
5.9%
F3
 
5.9%
N3
 
5.9%
T2
 
3.9%
I2
 
3.9%
B1
 
2.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
,4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin313
93.7%
Common21
 
6.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a41
13.1%
i36
11.5%
n32
 
10.2%
e25
 
8.0%
C19
 
6.1%
h19
 
6.1%
t18
 
5.8%
o13
 
4.2%
r13
 
4.2%
s12
 
3.8%
Other values (22)85
27.2%
Common
ValueCountFrequency (%)
17
81.0%
,4
 
19.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a41
12.3%
i36
 
10.8%
n32
 
9.6%
e25
 
7.5%
C19
 
5.7%
h19
 
5.7%
t18
 
5.4%
17
 
5.1%
o13
 
3.9%
r13
 
3.9%
Other values (24)101
30.2%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)23.7%
Missing55
Missing (%)59.1%
Memory size872.0 B
CN
19 
US
KR
RU
NO
Other values (4)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters76
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)7.9%

Sample

1st rowKR
2nd rowRU
3rd rowRU
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN19
 
20.4%
US5
 
5.4%
KR3
 
3.2%
RU3
 
3.2%
NO3
 
3.2%
TR2
 
2.2%
IR1
 
1.1%
BR1
 
1.1%
JP1
 
1.1%
(Missing)55
59.1%

Length

2022-09-05T21:39:42.109600image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:42.216772image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn19
50.0%
us5
 
13.2%
kr3
 
7.9%
ru3
 
7.9%
no3
 
7.9%
tr2
 
5.3%
ir1
 
2.6%
br1
 
2.6%
jp1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
N22
28.9%
C19
25.0%
R10
13.2%
U8
 
10.5%
S5
 
6.6%
K3
 
3.9%
O3
 
3.9%
T2
 
2.6%
I1
 
1.3%
B1
 
1.3%
Other values (2)2
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter76
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N22
28.9%
C19
25.0%
R10
13.2%
U8
 
10.5%
S5
 
6.6%
K3
 
3.9%
O3
 
3.9%
T2
 
2.6%
I1
 
1.3%
B1
 
1.3%
Other values (2)2
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Latin76
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N22
28.9%
C19
25.0%
R10
13.2%
U8
 
10.5%
S5
 
6.6%
K3
 
3.9%
O3
 
3.9%
T2
 
2.6%
I1
 
1.3%
B1
 
1.3%
Other values (2)2
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N22
28.9%
C19
25.0%
R10
13.2%
U8
 
10.5%
S5
 
6.6%
K3
 
3.9%
O3
 
3.9%
T2
 
2.6%
I1
 
1.3%
B1
 
1.3%
Other values (2)2
 
2.6%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)23.7%
Missing55
Missing (%)59.1%
Memory size872.0 B
Asia/Shanghai
19 
America/New_York
Asia/Seoul
Asia/Kamchatka
Europe/Oslo
Other values (4)

Length

Max length16
Median length15.5
Mean length13.10526316
Min length10

Characters and Unicode

Total characters498
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)7.9%

Sample

1st rowAsia/Seoul
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai19
 
20.4%
America/New_York5
 
5.4%
Asia/Seoul3
 
3.2%
Asia/Kamchatka3
 
3.2%
Europe/Oslo3
 
3.2%
Europe/Istanbul2
 
2.2%
Asia/Tehran1
 
1.1%
America/Noronha1
 
1.1%
Asia/Tokyo1
 
1.1%
(Missing)55
59.1%

Length

2022-09-05T21:39:42.316882image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:42.433326image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai19
50.0%
america/new_york5
 
13.2%
asia/seoul3
 
7.9%
asia/kamchatka3
 
7.9%
europe/oslo3
 
7.9%
europe/istanbul2
 
5.3%
asia/tehran1
 
2.6%
america/noronha1
 
2.6%
asia/tokyo1
 
2.6%

Most occurring characters

ValueCountFrequency (%)
a84
16.9%
i52
 
10.4%
h43
 
8.6%
/38
 
7.6%
A33
 
6.6%
s32
 
6.4%
n23
 
4.6%
S22
 
4.4%
o20
 
4.0%
e20
 
4.0%
Other values (20)131
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter374
75.1%
Uppercase Letter81
 
16.3%
Other Punctuation38
 
7.6%
Connector Punctuation5
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a84
22.5%
i52
13.9%
h43
11.5%
s32
 
8.6%
n23
 
6.1%
o20
 
5.3%
e20
 
5.3%
g19
 
5.1%
r18
 
4.8%
u10
 
2.7%
Other values (9)53
14.2%
Uppercase Letter
ValueCountFrequency (%)
A33
40.7%
S22
27.2%
N6
 
7.4%
E5
 
6.2%
Y5
 
6.2%
K3
 
3.7%
O3
 
3.7%
I2
 
2.5%
T2
 
2.5%
Other Punctuation
ValueCountFrequency (%)
/38
100.0%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin455
91.4%
Common43
 
8.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a84
18.5%
i52
11.4%
h43
9.5%
A33
 
7.3%
s32
 
7.0%
n23
 
5.1%
S22
 
4.8%
o20
 
4.4%
e20
 
4.4%
g19
 
4.2%
Other values (18)107
23.5%
Common
ValueCountFrequency (%)
/38
88.4%
_5
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII498
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a84
16.9%
i52
 
10.4%
h43
 
8.6%
/38
 
7.6%
A33
 
6.6%
s32
 
6.4%
n23
 
4.6%
S22
 
4.4%
o20
 
4.0%
e20
 
4.0%
Other values (20)131
26.3%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)15.4%
Missing28
Missing (%)30.1%
Memory size872.0 B
https://www.youtube.com
34 
https://v.qq.com/
16 
https://www.netflix.com/
https://www.iq.com/
 
3
https://tv.naver.com/
 
2
Other values (5)

Length

Max length30
Median length23
Mean length21.58461538
Min length17

Characters and Unicode

Total characters1403
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)7.7%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://www.youtube.com
3rd rowhttps://hd.kinopoisk.ru/
4th rowhttps://v.qq.com/
5th rowhttps://tv.naver.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com34
36.6%
https://v.qq.com/16
17.2%
https://www.netflix.com/5
 
5.4%
https://www.iq.com/3
 
3.2%
https://tv.naver.com/2
 
2.2%
https://www.vlive.tv/home1
 
1.1%
https://hd.kinopoisk.ru/1
 
1.1%
https://www.discoveryplus.com/1
 
1.1%
https://www.hulu.com/1
 
1.1%
https://www.paramountplus.com/1
 
1.1%
(Missing)28
30.1%

Length

2022-09-05T21:39:42.537308image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:42.644726image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com34
52.3%
https://v.qq.com16
24.6%
https://www.netflix.com5
 
7.7%
https://www.iq.com3
 
4.6%
https://tv.naver.com2
 
3.1%
https://www.vlive.tv/home1
 
1.5%
https://hd.kinopoisk.ru1
 
1.5%
https://www.discoveryplus.com1
 
1.5%
https://www.hulu.com1
 
1.5%
https://www.paramountplus.com1
 
1.5%

Most occurring characters

ValueCountFrequency (%)
t173
12.3%
/161
11.5%
w138
 
9.8%
.130
 
9.3%
o102
 
7.3%
u74
 
5.3%
p69
 
4.9%
s69
 
4.9%
h68
 
4.8%
:65
 
4.6%
Other values (16)354
25.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1047
74.6%
Other Punctuation356
 
25.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t173
16.5%
w138
13.2%
o102
9.7%
u74
7.1%
p69
 
6.6%
s69
 
6.6%
h68
 
6.5%
m65
 
6.2%
c64
 
6.1%
e44
 
4.2%
Other values (13)181
17.3%
Other Punctuation
ValueCountFrequency (%)
/161
45.2%
.130
36.5%
:65
18.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1047
74.6%
Common356
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t173
16.5%
w138
13.2%
o102
9.7%
u74
7.1%
p69
 
6.6%
s69
 
6.6%
h68
 
6.5%
m65
 
6.2%
c64
 
6.1%
e44
 
4.2%
Other values (13)181
17.3%
Common
ValueCountFrequency (%)
/161
45.2%
.130
36.5%
:65
18.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t173
12.3%
/161
11.5%
w138
 
9.8%
.130
 
9.3%
o102
 
7.3%
u74
 
5.3%
p69
 
4.9%
s69
 
4.9%
h68
 
4.8%
:65
 
4.6%
Other values (16)354
25.2%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing92
Missing (%)98.9%
Memory size872.0 B
19056.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row19056.0

Common Values

ValueCountFrequency (%)
19056.01
 
1.1%
(Missing)92
98.9%

Length

2022-09-05T21:39:42.733311image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:42.806822image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
19056.01
100.0%

Most occurring characters

ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02
33.3%
11
16.7%
91
16.7%
51
16.7%
61
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02
28.6%
11
14.3%
91
14.3%
51
14.3%
61
14.3%
.1
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)84.3%
Missing42
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean344514.1373
Minimum104271
Maximum395798
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:42.887731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum104271
5-th percentile265468.5
Q1308824
median364730
Q3389105.5
95-th percentile392665.5
Maximum395798
Range291527
Interquartile range (IQR)80281.5

Descriptive statistics

Standard deviation56761.29574
Coefficient of variation (CV)0.1647575226
Kurtosis4.891770733
Mean344514.1373
Median Absolute Deviation (MAD)26838
Skewness-1.833419868
Sum17570221
Variance3221844694
MonotonicityNot monotonic
2022-09-05T21:39:42.996144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
3522075
 
5.4%
2813452
 
2.2%
3923622
 
2.2%
3922142
 
2.2%
2787932
 
2.2%
3922381
 
1.1%
3744641
 
1.1%
3957981
 
1.1%
3725651
 
1.1%
3418001
 
1.1%
Other values (33)33
35.5%
(Missing)42
45.2%
ValueCountFrequency (%)
1042711
1.1%
2604361
1.1%
2651931
1.1%
2657441
1.1%
2682981
1.1%
2741751
1.1%
2743991
1.1%
2787932
2.2%
2813452
2.2%
2840461
1.1%
ValueCountFrequency (%)
3957981
1.1%
3940451
1.1%
3926821
1.1%
3926491
1.1%
3924551
1.1%
3923622
2.2%
3922381
1.1%
3922142
2.2%
3915681
1.1%
3910621
1.1%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING

Distinct33
Distinct (%)82.5%
Missing53
Missing (%)57.0%
Memory size872.0 B
tt8403536
tt1714810
 
2
tt13539710
 
2
tt10094402
 
2
tt4907178
 
1
Other values (28)
28 

Length

Max length10
Median length10
Mean length9.525
Min length9

Characters and Unicode

Total characters381
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)72.5%

Sample

1st rowtt15127174
2nd rowtt11492320
3rd rowtt11450050
4th rowtt13667230
5th rowtt4907178

Common Values

ValueCountFrequency (%)
tt84035365
 
5.4%
tt17148102
 
2.2%
tt135397102
 
2.2%
tt100944022
 
2.2%
tt49071781
 
1.1%
tt92067881
 
1.1%
tt00965971
 
1.1%
tt132805421
 
1.1%
tt109514381
 
1.1%
tt120266521
 
1.1%
Other values (23)23
24.7%
(Missing)53
57.0%

Length

2022-09-05T21:39:43.095301image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt84035365
 
12.5%
tt135397102
 
5.0%
tt100944022
 
5.0%
tt17148102
 
5.0%
tt122398241
 
2.5%
tt132548181
 
2.5%
tt151271741
 
2.5%
tt114923201
 
2.5%
tt112297481
 
2.5%
tt110924821
 
2.5%
Other values (23)23
57.5%

Most occurring characters

ValueCountFrequency (%)
t80
21.0%
151
13.4%
044
11.5%
333
8.7%
233
8.7%
829
 
7.6%
428
 
7.3%
624
 
6.3%
522
 
5.8%
920
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number301
79.0%
Lowercase Letter80
 
21.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
151
16.9%
044
14.6%
333
11.0%
233
11.0%
829
9.6%
428
9.3%
624
8.0%
522
7.3%
920
 
6.6%
717
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
t80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common301
79.0%
Latin80
 
21.0%

Most frequent character per script

Common
ValueCountFrequency (%)
151
16.9%
044
14.6%
333
11.0%
233
11.0%
829
9.6%
428
9.3%
624
8.0%
522
7.3%
920
 
6.6%
717
 
5.6%
Latin
ValueCountFrequency (%)
t80
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII381
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t80
21.0%
151
13.4%
044
11.5%
333
8.7%
233
8.7%
829
 
7.6%
428
 
7.3%
624
 
6.3%
522
 
5.8%
920
 
5.2%

_embedded.show.image.medium
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct62
Distinct (%)69.7%
Missing4
Missing (%)4.3%
Memory size872.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/275/688802.jpg
10 
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg
https://static.tvmaze.com/uploads/images/medium_portrait/198/495228.jpg
 
5
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg
 
2
Other values (57)
62 

Length

Max length72
Median length71
Mean length70.98876404
Min length70

Characters and Unicode

Total characters6318
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)58.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/275/688802.jpg10
 
10.8%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg8
 
8.6%
https://static.tvmaze.com/uploads/images/medium_portrait/198/495228.jpg5
 
5.4%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpg2
 
2.2%
Other values (52)52
55.9%
(Missing)4
 
4.3%

Length

2022-09-05T21:39:43.197148image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/275/688802.jpg10
 
11.2%
https://static.tvmaze.com/uploads/images/medium_portrait/288/721432.jpg8
 
9.0%
https://static.tvmaze.com/uploads/images/medium_portrait/198/495228.jpg5
 
5.6%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713100.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/714863.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713040.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/51/129595.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713120.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpg2
 
2.2%
Other values (52)52
58.4%

Most occurring characters

ValueCountFrequency (%)
/623
 
9.9%
t623
 
9.9%
a445
 
7.0%
m445
 
7.0%
p356
 
5.6%
s356
 
5.6%
i356
 
5.6%
.267
 
4.2%
e267
 
4.2%
o267
 
4.2%
Other values (22)2313
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4450
70.4%
Other Punctuation979
 
15.5%
Decimal Number800
 
12.7%
Connector Punctuation89
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t623
14.0%
a445
10.0%
m445
10.0%
p356
 
8.0%
s356
 
8.0%
i356
 
8.0%
e267
 
6.0%
o267
 
6.0%
d178
 
4.0%
u178
 
4.0%
Other values (8)979
22.0%
Decimal Number
ValueCountFrequency (%)
8125
15.6%
2117
14.6%
187
10.9%
582
10.2%
778
9.8%
371
8.9%
062
7.8%
962
7.8%
461
7.6%
655
6.9%
Other Punctuation
ValueCountFrequency (%)
/623
63.6%
.267
27.3%
:89
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4450
70.4%
Common1868
29.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t623
14.0%
a445
10.0%
m445
10.0%
p356
 
8.0%
s356
 
8.0%
i356
 
8.0%
e267
 
6.0%
o267
 
6.0%
d178
 
4.0%
u178
 
4.0%
Other values (8)979
22.0%
Common
ValueCountFrequency (%)
/623
33.4%
.267
14.3%
8125
 
6.7%
2117
 
6.3%
_89
 
4.8%
:89
 
4.8%
187
 
4.7%
582
 
4.4%
778
 
4.2%
371
 
3.8%
Other values (4)240
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/623
 
9.9%
t623
 
9.9%
a445
 
7.0%
m445
 
7.0%
p356
 
5.6%
s356
 
5.6%
i356
 
5.6%
.267
 
4.2%
e267
 
4.2%
o267
 
4.2%
Other values (22)2313
36.6%

_embedded.show.image.original
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct62
Distinct (%)69.7%
Missing4
Missing (%)4.3%
Memory size872.0 B
https://static.tvmaze.com/uploads/images/original_untouched/275/688802.jpg
10 
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg
https://static.tvmaze.com/uploads/images/original_untouched/198/495228.jpg
 
5
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg
 
2
Other values (57)
62 

Length

Max length75
Median length74
Mean length73.98876404
Min length73

Characters and Unicode

Total characters6585
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)58.4%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/275/688802.jpg10
 
10.8%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg8
 
8.6%
https://static.tvmaze.com/uploads/images/original_untouched/198/495228.jpg5
 
5.4%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg2
 
2.2%
Other values (52)52
55.9%
(Missing)4
 
4.3%

Length

2022-09-05T21:39:43.302061image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/275/688802.jpg10
 
11.2%
https://static.tvmaze.com/uploads/images/original_untouched/288/721432.jpg8
 
9.0%
https://static.tvmaze.com/uploads/images/original_untouched/198/495228.jpg5
 
5.6%
https://static.tvmaze.com/uploads/images/original_untouched/285/713100.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/714863.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713040.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/51/129595.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713120.jpg2
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg2
 
2.2%
Other values (52)52
58.4%

Most occurring characters

ValueCountFrequency (%)
/623
 
9.5%
t534
 
8.1%
a445
 
6.8%
s356
 
5.4%
i356
 
5.4%
o356
 
5.4%
p267
 
4.1%
c267
 
4.1%
.267
 
4.1%
g267
 
4.1%
Other values (23)2847
43.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4717
71.6%
Other Punctuation979
 
14.9%
Decimal Number800
 
12.1%
Connector Punctuation89
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t534
 
11.3%
a445
 
9.4%
s356
 
7.5%
i356
 
7.5%
o356
 
7.5%
p267
 
5.7%
c267
 
5.7%
g267
 
5.7%
m267
 
5.7%
e267
 
5.7%
Other values (9)1335
28.3%
Decimal Number
ValueCountFrequency (%)
8125
15.6%
2117
14.6%
187
10.9%
582
10.2%
778
9.8%
371
8.9%
062
7.8%
962
7.8%
461
7.6%
655
6.9%
Other Punctuation
ValueCountFrequency (%)
/623
63.6%
.267
27.3%
:89
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4717
71.6%
Common1868
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t534
 
11.3%
a445
 
9.4%
s356
 
7.5%
i356
 
7.5%
o356
 
7.5%
p267
 
5.7%
c267
 
5.7%
g267
 
5.7%
m267
 
5.7%
e267
 
5.7%
Other values (9)1335
28.3%
Common
ValueCountFrequency (%)
/623
33.4%
.267
14.3%
8125
 
6.7%
2117
 
6.3%
:89
 
4.8%
_89
 
4.8%
187
 
4.7%
582
 
4.4%
778
 
4.2%
371
 
3.8%
Other values (4)240
 
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6585
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/623
 
9.5%
t534
 
8.1%
a445
 
6.8%
s356
 
5.4%
i356
 
5.4%
o356
 
5.4%
p267
 
4.1%
c267
 
4.1%
.267
 
4.1%
g267
 
4.1%
Other values (23)2847
43.2%

_embedded.show.summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING

Distinct58
Distinct (%)69.0%
Missing9
Missing (%)9.7%
Memory size872.0 B
<p>World War Two dives into the history of one of the most devastating wars in human history. Indy Neidell, Spartacus Olsson and their team of dedicated historians cover the events of World War Two week by week in realtime. Additionally, we take an in-depth look at the war against humanity, key figures in all camps, military hardware, impact on culture, military strategies and life at the home fronts or under occupation.</p>
10 
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>
<p>Stand-up phenom Gabriel Iglesias stars in this series as a good-natured high school history teacher who tries to help gifted misfit kids.</p>
 
5
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>
 
2
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>
 
2
Other values (53)
57 

Length

Max length1483
Median length435
Mean length324.297619
Min length39

Characters and Unicode

Total characters27241
Distinct characters100
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)58.3%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>
3rd row<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>
4th row<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>
5th row<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>

Common Values

ValueCountFrequency (%)
<p>World War Two dives into the history of one of the most devastating wars in human history. Indy Neidell, Spartacus Olsson and their team of dedicated historians cover the events of World War Two week by week in realtime. Additionally, we take an in-depth look at the war against humanity, key figures in all camps, military hardware, impact on culture, military strategies and life at the home fronts or under occupation.</p>10
 
10.8%
<p>Two unlikely individuals join forces to find the truth behind a series of murders using an unconventional method. Chen Si, a female detective with a sense of justice, unexpectedly becomess partners with Yuan Shuai, a dream interpreter with a dark past.</p>8
 
8.6%
<p>Stand-up phenom Gabriel Iglesias stars in this series as a good-natured high school history teacher who tries to help gifted misfit kids.</p>5
 
5.4%
<p>Pan, a desolate plastic surgeon, lived a repetitive and boring life every day until a conspiracy happened. He woke up in an abandoned factory, and found that someone had replaced his identity with a face exactly like him. His world has been completely overturned and left in a perilous situation. Can he overcome the difficulties and peel away the truth? How would he regain his identity?</p>2
 
2.2%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.2%
<p>A story that follows people whose lives are entangled due to a complicated case. While investigating a drug cartel as an undercover cop, Yan Jin falls in love with the beautiful coffee shop owner Ji Xiao'ou.</p>2
 
2.2%
<p>Merchant Jiang Shuo and his odd specialist companion Qin Yi Heng purchase frequented houses to exchange them. In any case, alarming things start to occur and each spooky house is by all accounts part of a major riddle. Jiang Shuo, Yi Heng, and police officer Yuan Mu Qing attempt to understand the riddle.</p>2
 
2.2%
<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>2
 
2.2%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.2%
<p><b>Cheat</b> revolves around five main young characters; an innocent young man, Vee, who has had an unusual sheltered upbringing. Vee lives with his full-time guardian, an apostolic nun. The series concerns the effect that Vee has on 3 siblings: Dong, Jennifer, and Jay. The siblings live with their mother who dabbles in witchcraft. Their father, who is never seen, left the family to be with his Mistress who makes up the eighth character in the entire series.</p>1
 
1.1%
Other values (48)48
51.6%
(Missing)9
 
9.7%

Length

2022-09-05T21:39:43.434980image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the250
 
5.6%
of150
 
3.4%
and140
 
3.1%
a124
 
2.8%
in95
 
2.1%
to92
 
2.1%
with60
 
1.3%
is41
 
0.9%
war35
 
0.8%
an34
 
0.8%
Other values (1380)3449
77.2%

Most occurring characters

ValueCountFrequency (%)
4372
16.0%
e2607
 
9.6%
t1786
 
6.6%
a1669
 
6.1%
i1614
 
5.9%
o1527
 
5.6%
n1519
 
5.6%
s1370
 
5.0%
r1309
 
4.8%
h1009
 
3.7%
Other values (90)8459
31.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter20758
76.2%
Space Separator4386
 
16.1%
Uppercase Letter782
 
2.9%
Other Punctuation725
 
2.7%
Math Symbol482
 
1.8%
Dash Punctuation59
 
0.2%
Decimal Number28
 
0.1%
Other Letter13
 
< 0.1%
Close Punctuation3
 
< 0.1%
Open Punctuation3
 
< 0.1%
Other values (2)2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2607
12.6%
t1786
 
8.6%
a1669
 
8.0%
i1614
 
7.8%
o1527
 
7.4%
n1519
 
7.3%
s1370
 
6.6%
r1309
 
6.3%
h1009
 
4.9%
l845
 
4.1%
Other values (22)5503
26.5%
Uppercase Letter
ValueCountFrequency (%)
T99
 
12.7%
A72
 
9.2%
S72
 
9.2%
W62
 
7.9%
Y46
 
5.9%
I40
 
5.1%
C37
 
4.7%
D29
 
3.7%
H29
 
3.7%
N27
 
3.5%
Other values (17)269
34.4%
Other Letter
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%
Other Punctuation
ValueCountFrequency (%)
,302
41.7%
.216
29.8%
/125
17.2%
'42
 
5.8%
"11
 
1.5%
!9
 
1.2%
?8
 
1.1%
:7
 
1.0%
;3
 
0.4%
2
 
0.3%
Decimal Number
ValueCountFrequency (%)
010
35.7%
27
25.0%
16
21.4%
32
 
7.1%
81
 
3.6%
51
 
3.6%
41
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
-47
79.7%
9
 
15.3%
3
 
5.1%
Space Separator
ValueCountFrequency (%)
4372
99.7%
 14
 
0.3%
Math Symbol
ValueCountFrequency (%)
<241
50.0%
>241
50.0%
Close Punctuation
ValueCountFrequency (%)
)3
100.0%
Open Punctuation
ValueCountFrequency (%)
(3
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin21540
79.1%
Common5688
 
20.9%
Han13
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2607
12.1%
t1786
 
8.3%
a1669
 
7.7%
i1614
 
7.5%
o1527
 
7.1%
n1519
 
7.1%
s1370
 
6.4%
r1309
 
6.1%
h1009
 
4.7%
l845
 
3.9%
Other values (49)6285
29.2%
Common
ValueCountFrequency (%)
4372
76.9%
,302
 
5.3%
<241
 
4.2%
>241
 
4.2%
.216
 
3.8%
/125
 
2.2%
-47
 
0.8%
'42
 
0.7%
 14
 
0.2%
"11
 
0.2%
Other values (18)77
 
1.4%
Han
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII27190
99.8%
None23
 
0.1%
Punctuation15
 
0.1%
CJK13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4372
16.1%
e2607
 
9.6%
t1786
 
6.6%
a1669
 
6.1%
i1614
 
5.9%
o1527
 
5.6%
n1519
 
5.6%
s1370
 
5.0%
r1309
 
4.8%
h1009
 
3.7%
Other values (65)8408
30.9%
None
ValueCountFrequency (%)
 14
60.9%
ü2
 
8.7%
ø2
 
8.7%
ş1
 
4.3%
ö1
 
4.3%
Ç1
 
4.3%
å1
 
4.3%
é1
 
4.3%
Punctuation
ValueCountFrequency (%)
9
60.0%
3
 
20.0%
2
 
13.3%
1
 
6.7%
CJK
ValueCountFrequency (%)
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Other values (3)3
23.1%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct66
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1640741326
Minimum1604587119
Maximum1662380496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:43.561285image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1604587119
5-th percentile1608384954
Q11625280455
median1645718781
Q31661254717
95-th percentile1662262961
Maximum1662380496
Range57793377
Interquartile range (IQR)35974262

Descriptive statistics

Standard deviation19875953.12
Coefficient of variation (CV)0.01211400774
Kurtosis-1.223515698
Mean1640741326
Median Absolute Deviation (MAD)16148332
Skewness-0.5103801702
Sum1.525889433 × 1011
Variance3.950535123 × 1014
MonotonicityNot monotonic
2022-09-05T21:39:43.683817image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
166226296110
 
10.8%
16128425838
 
8.6%
16252804555
 
5.4%
16095351412
 
2.2%
16076979652
 
2.2%
16090607262
 
2.2%
16508264802
 
2.2%
16544453122
 
2.2%
16446505822
 
2.2%
16481900582
 
2.2%
Other values (56)56
60.2%
ValueCountFrequency (%)
16045871191
1.1%
16076979652
2.2%
16083343021
1.1%
16083529671
1.1%
16084062791
1.1%
16084990071
1.1%
16090607262
2.2%
16095351412
2.2%
16113514451
1.1%
16114368421
1.1%
ValueCountFrequency (%)
16623804961
 
1.1%
16623462771
 
1.1%
16623062101
 
1.1%
166226296110
10.8%
16622162831
 
1.1%
16621513691
 
1.1%
16619744211
 
1.1%
16619689571
 
1.1%
16618875351
 
1.1%
16618671131
 
1.1%

_embedded.show._links.self.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct66
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
https://api.tvmaze.com/shows/49147
10 
https://api.tvmaze.com/shows/52400
https://api.tvmaze.com/shows/41930
 
5
https://api.tvmaze.com/shows/52104
 
2
https://api.tvmaze.com/shows/52038
 
2
Other values (61)
66 

Length

Max length34
Median length34
Mean length33.97849462
Min length33

Characters and Unicode

Total characters3160
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)60.2%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/51065
3rd rowhttps://api.tvmaze.com/shows/52198
4th rowhttps://api.tvmaze.com/shows/52933
5th rowhttps://api.tvmaze.com/shows/51336

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/4914710
 
10.8%
https://api.tvmaze.com/shows/524008
 
8.6%
https://api.tvmaze.com/shows/419305
 
5.4%
https://api.tvmaze.com/shows/521042
 
2.2%
https://api.tvmaze.com/shows/520382
 
2.2%
https://api.tvmaze.com/shows/521592
 
2.2%
https://api.tvmaze.com/shows/521082
 
2.2%
https://api.tvmaze.com/shows/521072
 
2.2%
https://api.tvmaze.com/shows/501062
 
2.2%
https://api.tvmaze.com/shows/152502
 
2.2%
Other values (56)56
60.2%

Length

2022-09-05T21:39:43.783821image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/4914710
 
10.8%
https://api.tvmaze.com/shows/524008
 
8.6%
https://api.tvmaze.com/shows/419305
 
5.4%
https://api.tvmaze.com/shows/521042
 
2.2%
https://api.tvmaze.com/shows/520382
 
2.2%
https://api.tvmaze.com/shows/521592
 
2.2%
https://api.tvmaze.com/shows/521082
 
2.2%
https://api.tvmaze.com/shows/521072
 
2.2%
https://api.tvmaze.com/shows/501062
 
2.2%
https://api.tvmaze.com/shows/152502
 
2.2%
Other values (56)56
60.2%

Most occurring characters

ValueCountFrequency (%)
/372
 
11.8%
s279
 
8.8%
t279
 
8.8%
h186
 
5.9%
p186
 
5.9%
a186
 
5.9%
o186
 
5.9%
.186
 
5.9%
m186
 
5.9%
e93
 
2.9%
Other values (16)1021
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2046
64.7%
Other Punctuation651
 
20.6%
Decimal Number463
 
14.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s279
13.6%
t279
13.6%
h186
9.1%
p186
9.1%
a186
9.1%
o186
9.1%
m186
9.1%
e93
 
4.5%
w93
 
4.5%
c93
 
4.5%
Other values (3)279
13.6%
Decimal Number
ValueCountFrequency (%)
467
14.5%
566
14.3%
164
13.8%
057
12.3%
244
9.5%
342
9.1%
940
8.6%
631
6.7%
727
5.8%
825
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/372
57.1%
.186
28.6%
:93
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2046
64.7%
Common1114
35.3%

Most frequent character per script

Common
ValueCountFrequency (%)
/372
33.4%
.186
16.7%
:93
 
8.3%
467
 
6.0%
566
 
5.9%
164
 
5.7%
057
 
5.1%
244
 
3.9%
342
 
3.8%
940
 
3.6%
Other values (3)83
 
7.5%
Latin
ValueCountFrequency (%)
s279
13.6%
t279
13.6%
h186
9.1%
p186
9.1%
a186
9.1%
o186
9.1%
m186
9.1%
e93
 
4.5%
w93
 
4.5%
c93
 
4.5%
Other values (3)279
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/372
 
11.8%
s279
 
8.8%
t279
 
8.8%
h186
 
5.9%
p186
 
5.9%
a186
 
5.9%
o186
 
5.9%
.186
 
5.9%
m186
 
5.9%
e93
 
2.9%
Other values (16)1021
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct66
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size872.0 B
https://api.tvmaze.com/episodes/2386071
10 
https://api.tvmaze.com/episodes/1984963
https://api.tvmaze.com/episodes/1982624
 
5
https://api.tvmaze.com/episodes/1976054
 
2
https://api.tvmaze.com/episodes/1973545
 
2
Other values (61)
66 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3627
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)60.2%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/2007760
3rd rowhttps://api.tvmaze.com/episodes/1986873
4th rowhttps://api.tvmaze.com/episodes/2245512
5th rowhttps://api.tvmaze.com/episodes/1964569

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/238607110
 
10.8%
https://api.tvmaze.com/episodes/19849638
 
8.6%
https://api.tvmaze.com/episodes/19826245
 
5.4%
https://api.tvmaze.com/episodes/19760542
 
2.2%
https://api.tvmaze.com/episodes/19735452
 
2.2%
https://api.tvmaze.com/episodes/19776512
 
2.2%
https://api.tvmaze.com/episodes/19762022
 
2.2%
https://api.tvmaze.com/episodes/19761662
 
2.2%
https://api.tvmaze.com/episodes/19769342
 
2.2%
https://api.tvmaze.com/episodes/23012762
 
2.2%
Other values (56)56
60.2%

Length

2022-09-05T21:39:43.869107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/238607110
 
10.8%
https://api.tvmaze.com/episodes/19849638
 
8.6%
https://api.tvmaze.com/episodes/19826245
 
5.4%
https://api.tvmaze.com/episodes/19760542
 
2.2%
https://api.tvmaze.com/episodes/19735452
 
2.2%
https://api.tvmaze.com/episodes/19776512
 
2.2%
https://api.tvmaze.com/episodes/19762022
 
2.2%
https://api.tvmaze.com/episodes/19761662
 
2.2%
https://api.tvmaze.com/episodes/19769342
 
2.2%
https://api.tvmaze.com/episodes/23012762
 
2.2%
Other values (56)56
60.2%

Most occurring characters

ValueCountFrequency (%)
/372
 
10.3%
t279
 
7.7%
p279
 
7.7%
s279
 
7.7%
e279
 
7.7%
a186
 
5.1%
i186
 
5.1%
.186
 
5.1%
m186
 
5.1%
o186
 
5.1%
Other values (16)1209
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2325
64.1%
Other Punctuation651
 
17.9%
Decimal Number651
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t279
12.0%
p279
12.0%
s279
12.0%
e279
12.0%
a186
8.0%
i186
8.0%
m186
8.0%
o186
8.0%
h93
 
4.0%
d93
 
4.0%
Other values (3)279
12.0%
Decimal Number
ValueCountFrequency (%)
2115
17.7%
177
11.8%
973
11.2%
771
10.9%
667
10.3%
366
10.1%
858
8.9%
049
7.5%
442
 
6.5%
533
 
5.1%
Other Punctuation
ValueCountFrequency (%)
/372
57.1%
.186
28.6%
:93
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2325
64.1%
Common1302
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/372
28.6%
.186
14.3%
2115
 
8.8%
:93
 
7.1%
177
 
5.9%
973
 
5.6%
771
 
5.5%
667
 
5.1%
366
 
5.1%
858
 
4.5%
Other values (3)124
 
9.5%
Latin
ValueCountFrequency (%)
t279
12.0%
p279
12.0%
s279
12.0%
e279
12.0%
a186
8.0%
i186
8.0%
m186
8.0%
o186
8.0%
h93
 
4.0%
d93
 
4.0%
Other values (3)279
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3627
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/372
 
10.3%
t279
 
7.7%
p279
 
7.7%
s279
 
7.7%
e279
 
7.7%
a186
 
5.1%
i186
 
5.1%
.186
 
5.1%
m186
 
5.1%
o186
 
5.1%
Other values (16)1209
33.3%

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct30
Distinct (%)100.0%
Missing63
Missing (%)67.7%
Memory size872.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/288/720514.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/724606.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/289/724605.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/286/716333.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/359/897952.jpg
 
1
Other values (25)
25 

Length

Max length73
Median length72
Mean length72.06666667
Min length72

Characters and Unicode

Total characters2162
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737207.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726342.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719824.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/285/714315.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/287/719075.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/288/720514.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724606.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724605.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/286/716333.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/359/897952.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/717675.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/403/1009866.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/404/1012047.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/358/896917.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718754.jpg1
 
1.1%
Other values (20)20
 
21.5%
(Missing)63
67.7%

Length

2022-09-05T21:39:43.956390image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/288/720514.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724606.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726342.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719824.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/285/714315.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/287/719075.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718615.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718616.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718617.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/medium_landscape/287/718618.jpg1
 
3.3%
Other values (20)20
66.7%

Most occurring characters

ValueCountFrequency (%)
/210
 
9.7%
a180
 
8.3%
s150
 
6.9%
m150
 
6.9%
t150
 
6.9%
p120
 
5.6%
e120
 
5.6%
i90
 
4.2%
c90
 
4.2%
.90
 
4.2%
Other values (22)812
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1530
70.8%
Other Punctuation330
 
15.3%
Decimal Number272
 
12.6%
Connector Punctuation30
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a180
11.8%
s150
9.8%
m150
9.8%
t150
9.8%
p120
 
7.8%
e120
 
7.8%
i90
 
5.9%
c90
 
5.9%
d90
 
5.9%
l60
 
3.9%
Other values (8)330
21.6%
Decimal Number
ValueCountFrequency (%)
754
19.9%
847
17.3%
244
16.2%
128
10.3%
021
 
7.7%
919
 
7.0%
617
 
6.2%
515
 
5.5%
414
 
5.1%
313
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/210
63.6%
.90
27.3%
:30
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1530
70.8%
Common632
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a180
11.8%
s150
9.8%
m150
9.8%
t150
9.8%
p120
 
7.8%
e120
 
7.8%
i90
 
5.9%
c90
 
5.9%
d90
 
5.9%
l60
 
3.9%
Other values (8)330
21.6%
Common
ValueCountFrequency (%)
/210
33.2%
.90
14.2%
754
 
8.5%
847
 
7.4%
244
 
7.0%
_30
 
4.7%
:30
 
4.7%
128
 
4.4%
021
 
3.3%
919
 
3.0%
Other values (4)59
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2162
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/210
 
9.7%
a180
 
8.3%
s150
 
6.9%
m150
 
6.9%
t150
 
6.9%
p120
 
5.6%
e120
 
5.6%
i90
 
4.2%
c90
 
4.2%
.90
 
4.2%
Other values (22)812
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct30
Distinct (%)100.0%
Missing63
Missing (%)67.7%
Memory size872.0 B
https://static.tvmaze.com/uploads/images/original_untouched/288/720514.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/724606.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/289/724605.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/286/716333.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/359/897952.jpg
 
1
Other values (25)
25 

Length

Max length75
Median length74
Mean length74.06666667
Min length74

Characters and Unicode

Total characters2222
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/294/737207.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726342.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719824.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/285/714315.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/287/719075.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/288/720514.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/289/724606.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/289/724605.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/286/716333.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/359/897952.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/717675.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/403/1009866.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/404/1012047.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/358/896917.jpg1
 
1.1%
https://static.tvmaze.com/uploads/images/original_untouched/287/718754.jpg1
 
1.1%
Other values (20)20
 
21.5%
(Missing)63
67.7%

Length

2022-09-05T21:39:44.045699image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/288/720514.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/289/724606.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/290/726342.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/719824.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/285/714315.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/719075.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718615.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718616.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718617.jpg1
 
3.3%
https://static.tvmaze.com/uploads/images/original_untouched/287/718618.jpg1
 
3.3%
Other values (20)20
66.7%

Most occurring characters

ValueCountFrequency (%)
/210
 
9.5%
t180
 
8.1%
a150
 
6.8%
s120
 
5.4%
i120
 
5.4%
o120
 
5.4%
p90
 
4.1%
c90
 
4.1%
.90
 
4.1%
g90
 
4.1%
Other values (23)962
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1590
71.6%
Other Punctuation330
 
14.9%
Decimal Number272
 
12.2%
Connector Punctuation30
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t180
 
11.3%
a150
 
9.4%
s120
 
7.5%
i120
 
7.5%
o120
 
7.5%
p90
 
5.7%
c90
 
5.7%
g90
 
5.7%
m90
 
5.7%
e90
 
5.7%
Other values (9)450
28.3%
Decimal Number
ValueCountFrequency (%)
754
19.9%
847
17.3%
244
16.2%
128
10.3%
021
 
7.7%
919
 
7.0%
617
 
6.2%
515
 
5.5%
414
 
5.1%
313
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/210
63.6%
.90
27.3%
:30
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1590
71.6%
Common632
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t180
 
11.3%
a150
 
9.4%
s120
 
7.5%
i120
 
7.5%
o120
 
7.5%
p90
 
5.7%
c90
 
5.7%
g90
 
5.7%
m90
 
5.7%
e90
 
5.7%
Other values (9)450
28.3%
Common
ValueCountFrequency (%)
/210
33.2%
.90
14.2%
754
 
8.5%
847
 
7.4%
244
 
7.0%
:30
 
4.7%
_30
 
4.7%
128
 
4.4%
021
 
3.3%
919
 
3.0%
Other values (4)59
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/210
 
9.5%
t180
 
8.1%
a150
 
6.8%
s120
 
5.4%
i120
 
5.4%
o120
 
5.4%
p90
 
4.1%
c90
 
4.1%
.90
 
4.1%
g90
 
4.1%
Other values (23)962
43.3%

_embedded.show.network.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)90.9%
Missing82
Missing (%)88.2%
Infinite0
Infinite (%)0.0%
Mean452.8181818
Minimum85
Maximum1354
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size872.0 B
2022-09-05T21:39:44.120389image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum85
5-th percentile98.5
Q1182
median374
Q3473
95-th percentile1180
Maximum1354
Range1269
Interquartile range (IQR)291

Descriptive statistics

Standard deviation393.5890797
Coefficient of variation (CV)0.8691989312
Kurtosis1.919846942
Mean452.8181818
Median Absolute Deviation (MAD)169
Skewness1.539316354
Sum4981
Variance154912.3636
MonotonicityNot monotonic
2022-09-05T21:39:44.204049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4322
 
2.2%
3081
 
1.1%
5141
 
1.1%
851
 
1.1%
1591
 
1.1%
2051
 
1.1%
3741
 
1.1%
13541
 
1.1%
10061
 
1.1%
1121
 
1.1%
(Missing)82
88.2%
ValueCountFrequency (%)
851
1.1%
1121
1.1%
1591
1.1%
2051
1.1%
3081
1.1%
3741
1.1%
4322
2.2%
5141
1.1%
10061
1.1%
13541
1.1%
ValueCountFrequency (%)
13541
1.1%
10061
1.1%
5141
1.1%
4322
2.2%
3741
1.1%
3081
1.1%
2051
1.1%
1591
1.1%
1121
1.1%
851
1.1%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct10
Distinct (%)90.9%
Missing82
Missing (%)88.2%
Memory size872.0 B
OCS Max
ТНТ
ТВ-3
PBS
TBS
Other values (5)

Length

Max length11
Median length8
Mean length6.181818182
Min length3

Characters and Unicode

Total characters68
Distinct characters35
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)81.8%

Sample

1st rowТНТ
2nd rowТВ-3
3rd rowPBS
4th rowTBS
5th rowNFL Network

Common Values

ValueCountFrequency (%)
OCS Max2
 
2.2%
ТНТ1
 
1.1%
ТВ-31
 
1.1%
PBS1
 
1.1%
TBS1
 
1.1%
NFL Network1
 
1.1%
TV Globo1
 
1.1%
Fuji TV TWO1
 
1.1%
Vice TV1
 
1.1%
RTL41
 
1.1%
(Missing)82
88.2%

Length

2022-09-05T21:39:44.293455image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:44.401999image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tv3
16.7%
ocs2
11.1%
max2
11.1%
тнт1
 
5.6%
тв-31
 
5.6%
pbs1
 
5.6%
tbs1
 
5.6%
nfl1
 
5.6%
network1
 
5.6%
globo1
 
5.6%
Other values (4)4
22.2%

Most occurring characters

ValueCountFrequency (%)
7
 
10.3%
T6
 
8.8%
S4
 
5.9%
V4
 
5.9%
O3
 
4.4%
o3
 
4.4%
Т3
 
4.4%
B2
 
2.9%
i2
 
2.9%
e2
 
2.9%
Other values (25)32
47.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter38
55.9%
Lowercase Letter20
29.4%
Space Separator7
 
10.3%
Decimal Number2
 
2.9%
Dash Punctuation1
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T6
15.8%
S4
10.5%
V4
10.5%
O3
 
7.9%
Т3
 
7.9%
B2
 
5.3%
C2
 
5.3%
F2
 
5.3%
N2
 
5.3%
L2
 
5.3%
Other values (7)8
21.1%
Lowercase Letter
ValueCountFrequency (%)
o3
15.0%
i2
10.0%
e2
10.0%
a2
10.0%
x2
10.0%
c1
 
5.0%
j1
 
5.0%
u1
 
5.0%
b1
 
5.0%
l1
 
5.0%
Other values (4)4
20.0%
Decimal Number
ValueCountFrequency (%)
31
50.0%
41
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin53
77.9%
Common10
 
14.7%
Cyrillic5
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
T6
 
11.3%
S4
 
7.5%
V4
 
7.5%
O3
 
5.7%
o3
 
5.7%
B2
 
3.8%
i2
 
3.8%
e2
 
3.8%
C2
 
3.8%
F2
 
3.8%
Other values (18)23
43.4%
Common
ValueCountFrequency (%)
7
70.0%
31
 
10.0%
-1
 
10.0%
41
 
10.0%
Cyrillic
ValueCountFrequency (%)
Т3
60.0%
Н1
 
20.0%
В1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII63
92.6%
Cyrillic5
 
7.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
 
11.1%
T6
 
9.5%
S4
 
6.3%
V4
 
6.3%
O3
 
4.8%
o3
 
4.8%
B2
 
3.2%
i2
 
3.2%
e2
 
3.2%
C2
 
3.2%
Other values (22)28
44.4%
Cyrillic
ValueCountFrequency (%)
Т3
60.0%
Н1
 
20.0%
В1
 
20.0%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)54.5%
Missing82
Missing (%)88.2%
Memory size872.0 B
United States
Russian Federation
Japan
France
Brazil

Length

Max length18
Median length13
Mean length10.36363636
Min length5

Characters and Unicode

Total characters114
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st rowRussian Federation
2nd rowRussian Federation
3rd rowUnited States
4th rowJapan
5th rowUnited States

Common Values

ValueCountFrequency (%)
United States3
 
3.2%
Russian Federation2
 
2.2%
Japan2
 
2.2%
France2
 
2.2%
Brazil1
 
1.1%
Netherlands1
 
1.1%
(Missing)82
88.2%

Length

2022-09-05T21:39:44.497700image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:44.591076image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
united3
18.8%
states3
18.8%
russian2
12.5%
federation2
12.5%
japan2
12.5%
france2
12.5%
brazil1
 
6.2%
netherlands1
 
6.2%

Most occurring characters

ValueCountFrequency (%)
a15
13.2%
e14
12.3%
t12
10.5%
n12
10.5%
i8
 
7.0%
s8
 
7.0%
d6
 
5.3%
r6
 
5.3%
5
 
4.4%
F4
 
3.5%
Other values (13)24
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter93
81.6%
Uppercase Letter16
 
14.0%
Space Separator5
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a15
16.1%
e14
15.1%
t12
12.9%
n12
12.9%
i8
8.6%
s8
8.6%
d6
 
6.5%
r6
 
6.5%
p2
 
2.2%
l2
 
2.2%
Other values (5)8
8.6%
Uppercase Letter
ValueCountFrequency (%)
F4
25.0%
U3
18.8%
S3
18.8%
J2
12.5%
R2
12.5%
B1
 
6.2%
N1
 
6.2%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin109
95.6%
Common5
 
4.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a15
13.8%
e14
12.8%
t12
11.0%
n12
11.0%
i8
 
7.3%
s8
 
7.3%
d6
 
5.5%
r6
 
5.5%
F4
 
3.7%
U3
 
2.8%
Other values (12)21
19.3%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a15
13.2%
e14
12.3%
t12
10.5%
n12
10.5%
i8
 
7.0%
s8
 
7.0%
d6
 
5.3%
r6
 
5.3%
5
 
4.4%
F4
 
3.5%
Other values (13)24
21.1%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)54.5%
Missing82
Missing (%)88.2%
Memory size872.0 B
US
RU
JP
FR
BR

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters22
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st rowRU
2nd rowRU
3rd rowUS
4th rowJP
5th rowUS

Common Values

ValueCountFrequency (%)
US3
 
3.2%
RU2
 
2.2%
JP2
 
2.2%
FR2
 
2.2%
BR1
 
1.1%
NL1
 
1.1%
(Missing)82
88.2%

Length

2022-09-05T21:39:44.675062image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:44.771422image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
us3
27.3%
ru2
18.2%
jp2
18.2%
fr2
18.2%
br1
 
9.1%
nl1
 
9.1%

Most occurring characters

ValueCountFrequency (%)
U5
22.7%
R5
22.7%
S3
13.6%
J2
 
9.1%
P2
 
9.1%
F2
 
9.1%
B1
 
4.5%
N1
 
4.5%
L1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter22
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
U5
22.7%
R5
22.7%
S3
13.6%
J2
 
9.1%
P2
 
9.1%
F2
 
9.1%
B1
 
4.5%
N1
 
4.5%
L1
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Latin22
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U5
22.7%
R5
22.7%
S3
13.6%
J2
 
9.1%
P2
 
9.1%
F2
 
9.1%
B1
 
4.5%
N1
 
4.5%
L1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U5
22.7%
R5
22.7%
S3
13.6%
J2
 
9.1%
P2
 
9.1%
F2
 
9.1%
B1
 
4.5%
N1
 
4.5%
L1
 
4.5%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)54.5%
Missing82
Missing (%)88.2%
Memory size872.0 B
America/New_York
Asia/Kamchatka
Asia/Tokyo
Europe/Paris
America/Noronha

Length

Max length16
Median length15
Mean length13.72727273
Min length10

Characters and Unicode

Total characters151
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st rowAsia/Kamchatka
2nd rowAsia/Kamchatka
3rd rowAmerica/New_York
4th rowAsia/Tokyo
5th rowAmerica/New_York

Common Values

ValueCountFrequency (%)
America/New_York3
 
3.2%
Asia/Kamchatka2
 
2.2%
Asia/Tokyo2
 
2.2%
Europe/Paris2
 
2.2%
America/Noronha1
 
1.1%
Europe/Amsterdam1
 
1.1%
(Missing)82
88.2%

Length

2022-09-05T21:39:44.862006image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:44.964565image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
america/new_york3
27.3%
asia/kamchatka2
18.2%
asia/tokyo2
18.2%
europe/paris2
18.2%
america/noronha1
 
9.1%
europe/amsterdam1
 
9.1%

Most occurring characters

ValueCountFrequency (%)
a18
11.9%
r14
 
9.3%
o12
 
7.9%
e11
 
7.3%
/11
 
7.3%
i10
 
6.6%
A9
 
6.0%
m8
 
5.3%
s7
 
4.6%
k7
 
4.6%
Other values (16)44
29.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter112
74.2%
Uppercase Letter25
 
16.6%
Other Punctuation11
 
7.3%
Connector Punctuation3
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a18
16.1%
r14
12.5%
o12
10.7%
e11
9.8%
i10
8.9%
m8
7.1%
s7
 
6.2%
k7
 
6.2%
c6
 
5.4%
w3
 
2.7%
Other values (7)16
14.3%
Uppercase Letter
ValueCountFrequency (%)
A9
36.0%
N4
16.0%
Y3
 
12.0%
E3
 
12.0%
K2
 
8.0%
T2
 
8.0%
P2
 
8.0%
Other Punctuation
ValueCountFrequency (%)
/11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin137
90.7%
Common14
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a18
13.1%
r14
 
10.2%
o12
 
8.8%
e11
 
8.0%
i10
 
7.3%
A9
 
6.6%
m8
 
5.8%
s7
 
5.1%
k7
 
5.1%
c6
 
4.4%
Other values (14)35
25.5%
Common
ValueCountFrequency (%)
/11
78.6%
_3
 
21.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII151
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a18
11.9%
r14
 
9.3%
o12
 
7.9%
e11
 
7.3%
/11
 
7.3%
i10
 
6.6%
A9
 
6.0%
m8
 
5.3%
s7
 
4.6%
k7
 
4.6%
Other values (16)44
29.1%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct6
Distinct (%)100.0%
Missing87
Missing (%)93.5%
Memory size872.0 B
https://api.tvmaze.com/episodes/2309443
https://api.tvmaze.com/episodes/2384253
https://api.tvmaze.com/episodes/2375640
https://api.tvmaze.com/episodes/2383184
https://api.tvmaze.com/episodes/2383145

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters234
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2309443
2nd rowhttps://api.tvmaze.com/episodes/2384253
3rd rowhttps://api.tvmaze.com/episodes/2375640
4th rowhttps://api.tvmaze.com/episodes/2383184
5th rowhttps://api.tvmaze.com/episodes/2383145

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
 
1.1%
https://api.tvmaze.com/episodes/23842531
 
1.1%
https://api.tvmaze.com/episodes/23756401
 
1.1%
https://api.tvmaze.com/episodes/23831841
 
1.1%
https://api.tvmaze.com/episodes/23831451
 
1.1%
https://api.tvmaze.com/episodes/23797031
 
1.1%
(Missing)87
93.5%

Length

2022-09-05T21:39:45.053653image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:45.153619image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23094431
16.7%
https://api.tvmaze.com/episodes/23842531
16.7%
https://api.tvmaze.com/episodes/23756401
16.7%
https://api.tvmaze.com/episodes/23831841
16.7%
https://api.tvmaze.com/episodes/23831451
16.7%
https://api.tvmaze.com/episodes/23797031
16.7%

Most occurring characters

ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter150
64.1%
Other Punctuation42
 
17.9%
Decimal Number42
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%
Decimal Number
ValueCountFrequency (%)
311
26.2%
27
16.7%
46
14.3%
84
 
9.5%
03
 
7.1%
53
 
7.1%
73
 
7.1%
92
 
4.8%
12
 
4.8%
61
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/24
57.1%
.12
28.6%
:6
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin150
64.1%
Common84
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/24
28.6%
.12
14.3%
311
13.1%
27
 
8.3%
46
 
7.1%
:6
 
7.1%
84
 
4.8%
03
 
3.6%
53
 
3.6%
73
 
3.6%
Other values (3)5
 
6.0%
Latin
ValueCountFrequency (%)
p18
12.0%
s18
12.0%
e18
12.0%
t18
12.0%
a12
8.0%
i12
8.0%
m12
8.0%
o12
8.0%
h6
 
4.0%
d6
 
4.0%
Other values (3)18
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/24
 
10.3%
p18
 
7.7%
s18
 
7.7%
e18
 
7.7%
t18
 
7.7%
a12
 
5.1%
i12
 
5.1%
.12
 
5.1%
m12
 
5.1%
o12
 
5.1%
Other values (16)78
33.3%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing93
Missing (%)100.0%
Memory size872.0 B

_embedded.show.dvdCountry.name
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing92
Missing (%)98.9%
Memory size872.0 B
Japan

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowJapan

Common Values

ValueCountFrequency (%)
Japan1
 
1.1%
(Missing)92
98.9%

Length

2022-09-05T21:39:45.237843image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:45.315839image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
japan1
100.0%

Most occurring characters

ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4
80.0%
Uppercase Letter1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a2
50.0%
p1
25.0%
n1
25.0%
Uppercase Letter
ValueCountFrequency (%)
J1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a2
40.0%
J1
20.0%
p1
20.0%
n1
20.0%

_embedded.show.dvdCountry.code
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing92
Missing (%)98.9%
Memory size872.0 B
JP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowJP

Common Values

ValueCountFrequency (%)
JP1
 
1.1%
(Missing)92
98.9%

Length

2022-09-05T21:39:45.388978image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:45.469608image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
jp1
100.0%

Most occurring characters

ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J1
50.0%
P1
50.0%

_embedded.show.dvdCountry.timezone
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing92
Missing (%)98.9%
Memory size872.0 B
Asia/Tokyo

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAsia/Tokyo

Common Values

ValueCountFrequency (%)
Asia/Tokyo1
 
1.1%
(Missing)92
98.9%

Length

2022-09-05T21:39:45.542059image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:39:45.623412image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/tokyo1
100.0%

Most occurring characters

ValueCountFrequency (%)
o2
20.0%
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
T1
10.0%
k1
10.0%
y1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7
70.0%
Uppercase Letter2
 
20.0%
Other Punctuation1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2
28.6%
s1
14.3%
i1
14.3%
a1
14.3%
k1
14.3%
y1
14.3%
Uppercase Letter
ValueCountFrequency (%)
A1
50.0%
T1
50.0%
Other Punctuation
ValueCountFrequency (%)
/1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9
90.0%
Common1
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2
22.2%
A1
11.1%
s1
11.1%
i1
11.1%
a1
11.1%
T1
11.1%
k1
11.1%
y1
11.1%
Common
ValueCountFrequency (%)
/1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2
20.0%
A1
10.0%
s1
10.0%
i1
10.0%
a1
10.0%
/1
10.0%
T1
10.0%
k1
10.0%
y1
10.0%

Interactions

2022-09-05T21:39:32.357272image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:22.948743image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.890194image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.751027image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.628049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.505282image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.372678image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.228106image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.077609image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.871737image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.697042image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.536967image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:32.425467image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.120754image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.960329image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.824845image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.699376image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.568530image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.438924image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.297223image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.142841image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.934958image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.760509image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.600438image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.258951image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.202514image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.036154image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.908561image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.779313image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.638498image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.512337image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.374481image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.211203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.007068image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.831207image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.669932image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.337325image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.279072image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.108912image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.983518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.853396image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.712161image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.585807image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.447151image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.276751image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.074216image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.904008image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.740671image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.406544image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.350439image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.185485image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.058126image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.920681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.782014image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.666125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.524354image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.340511image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.139384image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.969842image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.805742image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.471523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.429005image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.253623image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.132782image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.987332image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.858992image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.738840image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.595118image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.409765image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.206376image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.036499image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.871218image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.543271image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.495073image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.322694image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.200248image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.061015image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.940900image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.812057image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.664456image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.480481image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.275549image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.110087image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.947260image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.612288image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.563173image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.395100image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.268237image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.135884image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.017030image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.884782image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.736631image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.549453image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.345731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.181971image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:32.018092image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.673317image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.626700image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.459886image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.334898image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.210883image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.103190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.951548image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.801540image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.612245image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.412529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.251347image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:32.083686image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.741912image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:39:24.526814image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.401795image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.292624image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.171222image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.018853image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.868755image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:39:35.813027image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.753524image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.602295image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.471144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.367169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
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2022-09-05T21:39:28.091394image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.942689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.744432image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.560110image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.401721image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:32.227586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:35.878666image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:23.819883image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:24.676237image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:25.545768image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:26.434785image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:27.304188image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:28.160087image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.010223image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:29.809360image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:30.625688image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:31.469703image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2022-09-05T21:39:32.293964image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:39:45.718825image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:39:45.981346image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:39:46.231670image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:39:46.519697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:39:36.239782image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:39:36.984290image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:39:37.544523image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

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01988857https://www.tvmaze.com/episodes/1988857/sim-for-you-4x19-chanyeols-episode-19Chanyeol's Episode 19419.0regular2020-12-0806:002020-12-07T21:00:00+00:0016.0NaN<p><b>#Camping Decoration #Did You Come Sehun?</b></p>NaNhttps://api.tvmaze.com/episodes/198885741648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637[Monday, Wednesday, Friday]NaN29NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNaNNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007https://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
12007748https://www.tvmaze.com/episodes/2007748/stand-up-autsajd-1x08-vana-ilin-malenkij-princВаня Ильин "Маленький принц"18.0regular2020-12-0812:002020-12-08T00:00:00+00:0024.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200774851065https://www.tvmaze.com/shows/51065/stand-up-autsajdStand Up АутсайдVarietyRussian[]Ended40.028.02020-10-132020-12-31https://premier.one/show/13734[Monday]NaN4NaN21.0YouTubeNaNNaNNaNhttps://www.youtube.comNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/277/693293.jpghttps://static.tvmaze.com/uploads/images/original_untouched/277/693293.jpg<p>Solo performances of stand-up comedians from the underground and popular TV and Internet projects. Each new release is a new concert with its own atmosphere and humor.</p>1616719192https://api.tvmaze.com/shows/51065https://api.tvmaze.com/episodes/2007760NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21986870https://www.tvmaze.com/episodes/1986870/kotiki-1x07-seria-7Серия 717.0regular2020-12-082020-12-08T00:00:00+00:0013.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198687052198https://www.tvmaze.com/shows/52198/kotikiКотикиScriptedRussian[Comedy]Ended12.012.02020-11-302020-12-11http://epic-media.ru/project/kotiki10:00[Monday, Tuesday, Wednesday, Thursday, Friday]NaN15NaN510.0Epic MediaRussian FederationRUAsia/KamchatkaNoneNaNNaN392682.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888089.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888089.jpgNone1637555191https://api.tvmaze.com/shows/52198https://api.tvmaze.com/episodes/1986873NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
32008028https://www.tvmaze.com/episodes/2008028/lab-s-antonom-belaevym-2x07-lev-lesenkoЛев Лещенко27.0regular2020-12-082020-12-08T00:00:00+00:0026.0NaNNoneNaNhttps://api.tvmaze.com/episodes/200802852933https://www.tvmaze.com/shows/52933/lab-s-antonom-belaevymLAB с Антоном БеляевымDocumentaryRussian[Music]To Be Determined26.025.02019-12-17Nonehttps://premier.one/show/lab-laboratoriya-muzyki-antona-belyaeva23:45[Saturday]NaN25NaN381.0КиноПоиск HDRussian FederationRUAsia/Kamchatkahttps://hd.kinopoisk.ru/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/379/948045.jpghttps://static.tvmaze.com/uploads/images/original_untouched/379/948045.jpg<p>Russian music artists reveal themselves from unexpected sides in the Anton Belyaev's show.</p>1654035738https://api.tvmaze.com/shows/52933https://api.tvmaze.com/episodes/2245512NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/294/737207.jpghttps://static.tvmaze.com/uploads/images/original_untouched/294/737207.jpg308.0ТНТRussian FederationRUAsia/KamchatkaNaNNaNNaNNaNNaNNaNNaN
41964566https://www.tvmaze.com/episodes/1964566/core-sense-1x10-episode-10Episode 10110.0regular2020-12-0810:002020-12-08T02:00:00+00:0024.0NaNNoneNaNhttps://api.tvmaze.com/episodes/196456651336https://www.tvmaze.com/shows/51336/core-senseCore SenseAnimationChinese[Action, Anime, Science-Fiction]Running24.024.02020-10-13Nonehttps://www.bilibili.com/bangumi/media/md2822306410:00[Tuesday]NaN29NaN51.0BilibiliChinaCNAsia/ShanghaiNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/278/696645.jpghttps://static.tvmaze.com/uploads/images/original_untouched/278/696645.jpg<p>The power of beginnings, the energy of the core stone; one may find it good, one may find it evil. During a normal investigation, Yue Juntian finds himself drawn into the battle between the 'beginnings' of Yun City; Jiang Xin arrives in Yun City to stop Li Zunyuan's plan to take over. The two influence each other - one solves the mystery of their birth, the other redeems themselves. Together, they oppose Li Zunyuan.<br /> </p>1604587119https://api.tvmaze.com/shows/51336https://api.tvmaze.com/episodes/1964569NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52052507https://www.tvmaze.com/episodes/2052507/wu-shen-zhu-zai-1x82-episode-82Episode 82182.0regular2020-12-0810:002020-12-08T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/205250754033https://www.tvmaze.com/shows/54033/wu-shen-zhu-zaiWu Shen Zhu ZaiAnimationChinese[Action, Adventure, Anime, Fantasy]Running8.08.02020-03-08Nonehttps://v.qq.com/detail/m/7q544xyrava3vxf.html10:00[Tuesday, Sunday]NaN82NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN379070.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/299/748854.jpghttps://static.tvmaze.com/uploads/images/original_untouched/299/748854.jpg<p>The protagonist Qin Chen, who was originally the top genius in the military domain, was conspired by the people to fall into the death canyon in the forbidden land of the mainland. Qin Chen, who was inevitably dead, unexpectedly triggered the power of the mysterious ancient sword.<br /><br />Three hundred years later, in a remote part of the Tianwu mainland, a boy of the same name accidentally inherited Qin Chen's will. As the beloved grandson of King Dingwu of the Daqi National Army, due to the birth father's birth, the mother and son were treated coldly in Dingwu's palace and lived together. In order to rewrite the myth of the strong man in hope of the sun, and to protect everything he loves, Qin Chen resolutely took up the responsibility of maintaining the five kingdoms of the world and set foot on the road of martial arts again.</p>1649423444https://api.tvmaze.com/shows/54033https://api.tvmaze.com/episodes/2309442NaNNaNNaNNaNNaNNaNNaNNaNNaNhttps://api.tvmaze.com/episodes/2309443NaNNaNNaNNaNNaN
62096295https://www.tvmaze.com/episodes/2096295/no-turning-back-romance-1x01-1111.0regular2020-12-082020-12-08T03:00:00+00:0012.0NaNNoneNaNhttps://api.tvmaze.com/episodes/209629555002https://www.tvmaze.com/shows/55002/no-turning-back-romanceNo Turning Back RomanceScriptedKorean[]EndedNaN12.02020-12-082021-01-06None[Tuesday, Wednesday]NaN23NaN30.0Naver TVCastKorea, Republic ofKRAsia/Seoulhttps://tv.naver.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/319/799196.jpghttps://static.tvmaze.com/uploads/images/original_untouched/319/799196.jpg<p>A teen romance of So Dam, a sixteen-year-old girl, who has never dated before but she receives her first-ever love confession from a mysterious boy. She is looking for the boy who secretly confessed to her while she was asleep on her desk. The clues include a male voice, mango fruit scent and gym uniform. She must piece the puzzle to find that person among the likely candidates that include hot shots Park Ji Hoo, Jeong Han Kyul, and Joo In Hyuk.</p>1621617231https://api.tvmaze.com/shows/55002https://api.tvmaze.com/episodes/2096309NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71973544https://www.tvmaze.com/episodes/1973544/please-wait-brother-1x23-episode-23Episode 23123.0regular2020-12-0812:002020-12-08T04:00:00+00:0037.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197354452038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None12:00[Tuesday, Wednesday, Thursday]NaN21NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpgNone1607697965https://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81973545https://www.tvmaze.com/episodes/1973545/please-wait-brother-1x24-episode-24Episode 24124.0regular2020-12-0812:002020-12-08T04:00:00+00:0037.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197354552038https://www.tvmaze.com/shows/52038/please-wait-brotherPlease Wait, BrotherScriptedChinese[Comedy]Ended37.037.02020-11-172020-12-08None12:00[Tuesday, Wednesday, Thursday]NaN21NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/284/711240.jpghttps://static.tvmaze.com/uploads/images/original_untouched/284/711240.jpgNone1607697965https://api.tvmaze.com/shows/52038https://api.tvmaze.com/episodes/1973545NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92082173https://www.tvmaze.com/episodes/2082173/ling-jian-zun-4x30-di130ji第130集430.0regular2020-12-082020-12-08T04:00:00+00:0010.0NaNNoneNaNhttps://api.tvmaze.com/episodes/208217355016https://www.tvmaze.com/shows/55016/ling-jian-zunLing Jian ZunAnimationChinese[Anime]Running10.010.02019-01-15Nonehttps://v.qq.com/x/cover/2w2legt0g8z26al.html[Tuesday, Friday]NaN52NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NaNNaN364730.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/311/778535.jpghttps://static.tvmaze.com/uploads/images/original_untouched/311/778535.jpg<p>The strong man was attacked and returned to his youth. He became the weakest waste young lord. He will never let go of the enemy of the previous life in this life and must make up the regret of the previous life in this life! By the time the Spirit Sword is powerful, the protagonist will be supreme in the three worlds between heaven and earth! If there is someone doesn't obey him, he will kill him with the sword!</p><p><br /> </p>1653895786https://api.tvmaze.com/shows/55016https://api.tvmaze.com/episodes/2336755NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.href_embedded.show.webChannel.countryimage.mediumimage.original_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.webChannel_embedded.show.dvdCountry.name_embedded.show.dvdCountry.code_embedded.show.dvdCountry.timezone
832311018https://www.tvmaze.com/episodes/2311018/toki-wo-kakeru-bando-1x08-chahhanryo-yukishioritohkoCHAHHAN&RYO YUKI&SHIORI&TOHKO18.0regular2020-12-0800:252020-12-08T15:25:00+00:0026.0NaN<p>After listening to the original song of 'No. 77', 'Yuki Ebana' was convinced that it was a song she sang for herself, and headed to the place where she used to live on the street, where she sang 'No. 77'. Discover the boy. The song 'No. 77' was made with the boy's singing in mind, Yuki.<br />Yuki tells her boy that their debut song is 'No. 77' made by the boy, and she takes the boy to meet her office president 'Yuichi Yanagishita'. The boy and Yanagishita will have a discussion together.<br />She returns and she tells the story to 'Ryo', 'Shiori Kato' and 'Hitoko Murakami'. Hitoko wonders if the boy is destined for Yuki. Ryo tells us that he wants to see you guys debut and play an active part as soon as possible, even if it's a human song.<br />However, the boy did not respond to Yanagishita's persuasion, and he refused to let him use his song. Ryo appeared to Yanagishita who was in trouble and said, 'Leave him to me.'</p>NaNhttps://api.tvmaze.com/episodes/231101861530https://www.tvmaze.com/shows/61530/toki-wo-kakeru-bandoToki wo Kakeru BandoScriptedJapanese[Comedy, Music, Science-Fiction]Ended27.026.02020-10-202020-12-22https://www.fujitv.co.jp/tokikake/00:25[Tuesday]NaN1NaN119.0FODJapanJPAsia/TokyoNoneNaNNaNNaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/403/1009836.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009836.jpg<p>A story about Ryo, a mysterious and self-proclaimed music producer from the future, producing a girl band of three girls and leading them to stardom. A comical and tempo conversational drama, and various trials to produce the youth of young people who play music with comedy touch.</p>1649705311https://api.tvmaze.com/shows/61530https://api.tvmaze.com/episodes/2311020NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/403/1009866.jpghttps://static.tvmaze.com/uploads/images/original_untouched/403/1009866.jpg1354.0Fuji TV TWOJapanJPAsia/TokyoNaNNaNNaNNaNJapanJPAsia/Tokyo
842165006https://www.tvmaze.com/episodes/2165006/all-about-android-2020-12-08-google-killed-what-nowGoogle Killed What Now?202049.0regular2020-12-082020-12-08T17:00:00+00:0090.0NaNNoneNaNhttps://api.tvmaze.com/episodes/216500617633https://www.tvmaze.com/shows/17633/all-about-androidAll About AndroidNewsEnglish[]RunningNaN90.02011-03-29Nonehttps://twit.tv/shows/all-about-android[Tuesday]NaN44NaN102.0TwitUnited StatesUSAmerica/New_YorkNoneNaNNaN260436.0tt3589312https://static.tvmaze.com/uploads/images/medium_portrait/59/148354.jpghttps://static.tvmaze.com/uploads/images/original_untouched/59/148354.jpg<p><b>All About Android </b>delivers everything you want to know about Android each week -- the biggest news, freshest hardware, best apps and geekiest how-to's -- with Android enthusiasts Jason Howell, Florence Ion, Ron Richards, and a variety of special guests along the way.</p>1653765273https://api.tvmaze.com/shows/17633https://api.tvmaze.com/episodes/2335726NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
851967349https://www.tvmaze.com/episodes/1967349/a-teacher-1x07-episode-7Episode 717.0regular2020-12-082020-12-08T17:00:00+00:0030.0NaN<p>Eric tries to move on, but fallout from the affair continues to resurface in unexpected ways.</p>7.2https://api.tvmaze.com/episodes/196734938339https://www.tvmaze.com/shows/38339/a-teacherA TeacherScriptedEnglish[Drama]EndedNaN27.02020-11-102020-12-29https://www.hulu.com/series/a-teacher-1c871218-05b1-4c66-a22f-260b2cb9bbf9[Tuesday]5.894NaN2.0HuluUnited StatesUSAmerica/New_Yorkhttps://www.hulu.com/NaNNaN352440.0tt10680614https://static.tvmaze.com/uploads/images/medium_portrait/272/681431.jpghttps://static.tvmaze.com/uploads/images/original_untouched/272/681431.jpg<p><b>A Teacher</b> examines the complexities and consequences of an illegal relationship between a female teacher, Claire and her male high school student, Eric. Dissatisfied in their own lives, Claire and Eric discover an undeniable escape in each other, but their relationship accelerates faster than anticipated and the permanent damage becomes impossible to ignore.</p>1637344861https://api.tvmaze.com/shows/38339https://api.tvmaze.com/episodes/1968004NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/287/717675.jpghttps://static.tvmaze.com/uploads/images/original_untouched/287/717675.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
861982592https://www.tvmaze.com/episodes/1982592/tooning-out-the-news-1x109-big-news"Big News"1109.0regular2020-12-082020-12-08T17:00:00+00:007.0NaN<p>Big News calls Rudy Giuliani to wish him a speedy recovery while Pulitzer-winning journalist Clarence Page joins the show to discuss the Covid crisis and Trump's post-presidency plans. </p>NaNhttps://api.tvmaze.com/episodes/198259245812https://www.tvmaze.com/shows/45812/tooning-out-the-newsTooning Out the NewsAnimationEnglish[Comedy]RunningNaN13.02020-04-07Nonehttps://www.paramountplus.com/shows/tooning-out-the-news/[Monday, Tuesday, Wednesday, Thursday, Friday]NaN41NaN107.0Paramount+NaNNaNNaNhttps://www.paramountplus.com/NaNNaN375994.0tt12026652https://static.tvmaze.com/uploads/images/medium_portrait/245/614061.jpghttps://static.tvmaze.com/uploads/images/original_untouched/245/614061.jpg<p><b>Tooning Out the News</b> will provide short daily segments leading up to a weekly full episodes featuring a cast of animated characters mocking news of the day, and interviewing real-world guests and newsmakers.</p>1636747761https://api.tvmaze.com/shows/45812https://api.tvmaze.com/episodes/2215367NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
871979394https://www.tvmaze.com/episodes/1979394/i-was-a-teenage-felon-1x10-have-drugs-will-travelHave Drugs, Will Travel110.0regular2020-12-082020-12-08T17:00:00+00:0060.0NaN<p>At age 17, Seth was living a rock star life while supplying 15 colleges in 5 different states, with massive amounts of acid and weed until the US Marshalls set their sites on him.</p>NaNhttps://api.tvmaze.com/episodes/197939450661https://www.tvmaze.com/shows/50661/i-was-a-teenage-felonI Was a Teenage FelonDocumentaryEnglish[Crime]Running60.060.02020-09-22Nonehttps://video.vice.com/en_us/show/i-was-a-teenage-felon[Monday]NaN41NaNNaNNaNNaNNaNNaNNaNNaNNaN385432.0tt10951438https://static.tvmaze.com/uploads/images/medium_portrait/371/929339.jpghttps://static.tvmaze.com/uploads/images/original_untouched/371/929339.jpg<p>Former criminals tell the true tales of their rollercoaster ride from average American kids to wildly successful outlaws.</p>1637762524https://api.tvmaze.com/shows/50661https://api.tvmaze.com/episodes/2207417NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/359/897952.jpghttps://static.tvmaze.com/uploads/images/original_untouched/359/897952.jpg1006.0Vice TVUnited StatesUSAmerica/New_YorkNaNNaNNaNNaNNaNNaNNaN
882380806https://www.tvmaze.com/episodes/2380806/dimension-20s-adventuring-party-3x03-the-yellow-mm-is-the-funniest-guy-aliveThe Yellow M&M Is the Funniest Guy Alive33.0regular2020-12-082020-12-08T17:00:00+00:0057.0NaNNoneNaNhttps://api.tvmaze.com/episodes/238080663761https://www.tvmaze.com/shows/63761/dimension-20s-adventuring-partyDimension 20's Adventuring PartyTalk ShowEnglish[]Running57.057.02020-04-08NoneNone[]NaN7NaN311.0DropoutUnited StatesUSAmerica/New_YorkNoneNaNNaN391568.0tt13280542https://static.tvmaze.com/uploads/images/medium_portrait/420/1050072.jpghttps://static.tvmaze.com/uploads/images/original_untouched/420/1050072.jpg<p>Adventuring Party is a series of livestreamed talk-back episodes that aired after each new episode of A Crown of Candy. An additional episode was pre-recorded featuring the Pirates of Leviathan following the release of episode 4. Each Adventuring Party episode features the Dimension 20 cast as they talk about the events of the most recent episode, their experiences during that session, any unique challenges or situations they encountered, and answer as many fan questions as Brennan allows.</p><p><br /> </p>1661532809https://api.tvmaze.com/shows/63761https://api.tvmaze.com/episodes/2380882NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
891960032https://www.tvmaze.com/episodes/1960032/goede-tijden-slechte-tijden-31x58-aflevering-6313Aflevering 63133158.0regular2020-12-0820:002020-12-08T19:00:00+00:0023.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19600322504https://www.tvmaze.com/shows/2504/goede-tijden-slechte-tijdenGoede Tijden, Slechte TijdenScriptedDutch[Drama, Romance]Running23.025.01990-10-01Nonehttp://gtst.nl/#!/20:00[Monday, Tuesday, Wednesday, Thursday]NaN83NaNNaNNaNNaNNaNNaNNaNNaN19056.0104271.0tt0096597https://static.tvmaze.com/uploads/images/medium_portrait/332/830481.jpghttps://static.tvmaze.com/uploads/images/original_untouched/332/830481.jpgNone1662346277https://api.tvmaze.com/shows/2504https://api.tvmaze.com/episodes/2379702NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/286/716333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/286/716333.jpg112.0RTL4NetherlandsNLEurope/AmsterdamNaNhttps://api.tvmaze.com/episodes/2379703NaNNaNNaNNaNNaN
901976931https://www.tvmaze.com/episodes/1976931/cheyenne-et-lola-1x05-a-la-vie-a-la-mortÀ la vie à la mort15.0regular2020-12-0820:402020-12-08T19:40:00+00:0050.0NaN<p>Le mari de Cheyenne, Joël Barden, s'est évadé de prison. Il refuse de partir en cavale sans elle avec la BRB aux trousses.</p>NaNhttps://api.tvmaze.com/episodes/197693150106https://www.tvmaze.com/shows/50106/cheyenne-et-lolaCheyenne et LolaScriptedFrench[Drama, Comedy, Crime]Running50.050.02020-11-24Nonehttps://go.ocs.fr/details/serie/PSCHEYENNEEW016825920:40[Tuesday]NaN40NaNNaNNaNNaNNaNNaNNaNNaNNaN281345.0tt10094402https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>1644650582https://api.tvmaze.com/shows/50106https://api.tvmaze.com/episodes/1976934NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724605.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724605.jpg432.0OCS MaxFranceFREurope/ParisNaNNaNNaNNaNNaNNaNNaN
911976932https://www.tvmaze.com/episodes/1976932/cheyenne-et-lola-1x06-dancing-queenDancing Queen16.0regular2020-12-0820:402020-12-08T19:40:00+00:0050.0NaN<p>Menacée par Lola qui lui en veut d'avoir trahi Cheyenne, Rachida sort un atout de dernière minute de sa manche.</p>NaNhttps://api.tvmaze.com/episodes/197693250106https://www.tvmaze.com/shows/50106/cheyenne-et-lolaCheyenne et LolaScriptedFrench[Drama, Comedy, Crime]Running50.050.02020-11-24Nonehttps://go.ocs.fr/details/serie/PSCHEYENNEEW016825920:40[Tuesday]NaN40NaNNaNNaNNaNNaNNaNNaNNaNNaN281345.0tt10094402https://static.tvmaze.com/uploads/images/medium_portrait/285/713798.jpghttps://static.tvmaze.com/uploads/images/original_untouched/285/713798.jpg<p>Cheyenne has been out of jail for six months now, working as a cleaner on the ferries whilst dreaming about traveling to the Amazon. Lola is a beautiful Parisian woman, selfish and ruthless, who has just arrived in the north of France to move in with her lover. But when Cheyenne witnesses Lola killing her lover's wife, she knows she's going to be accused of the crime because of her criminal past.</p>1644650582https://api.tvmaze.com/shows/50106https://api.tvmaze.com/episodes/1976934NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/289/724606.jpghttps://static.tvmaze.com/uploads/images/original_untouched/289/724606.jpg432.0OCS MaxFranceFREurope/ParisNaNNaNNaNNaNNaNNaNNaN
921983437https://www.tvmaze.com/episodes/1983437/chicken-girls-7x14-regionalsRegionals714.0regular2020-12-0815:002020-12-08T20:00:00+00:0016.0NaN<p>Tempers flare as the A Team and Millwood face off at Regionals and the boys have an eye-opening camping trip that has everyone choosing sides. </p>NaNhttps://api.tvmaze.com/episodes/198343732087https://www.tvmaze.com/shows/32087/chicken-girlsChicken GirlsScriptedEnglish[Drama, Music]RunningNaN14.02017-09-05Nonehttps://www.youtube.com/playlist?list=PLVewHiZp3_LPhqzbcZFmS3iuDm9HymTsy15:00[Tuesday]5.687NaN274.0BratUnited StatesUSAmerica/New_YorkNoneNaNNaN339854.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/355/888874.jpghttps://static.tvmaze.com/uploads/images/original_untouched/355/888874.jpg<p>Rhyme and her friends — known by their 'ship name, "The Chicken Girls" — have been dancing together forever. But this year, everything's changing...</p>1661790437https://api.tvmaze.com/shows/32087https://api.tvmaze.com/episodes/2270191NaNhttps://static.tvmaze.com/uploads/images/medium_landscape/369/923710.jpghttps://static.tvmaze.com/uploads/images/original_untouched/369/923710.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN